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IUI Tables of Contents: 0001020304050607080910111213-113-214-114-215-115-216-116-2

Proceedings of the 2010 International Conference on Intelligent User Interfaces

Fullname:International Conference on Intelligent User Interfaces
Editors:Charles Rich; Qiang Yang; Marc Cavazza; Michelle Zhou
Location:Hong Kong, China
Dates:2010-Feb-07 to 2010-Feb-10
Standard No:ISBN: 1-60558-515-7, 978-1-60558-515-4; ACM DL: Table of Contents hcibib: IUI10
Links:Conference Home Page
  1. Access/brain interfaces
  2. Smart reading
  3. Intelligent agent
  4. Mobile interaction
  5. Multimodal interaction
  6. Smart web apps
  7. Enhanced search
  8. UI for the masses
  9. User-centered design
  10. Short paper presentations (posters)
  11. Demonstrations
  12. Workshops

Access/brain interfaces

A POMDP approach to P300-based brain-computer interfaces BIBAKFull-Text 1-10
  Jaeyoung Park; Kee-Eung Kim; Sungho Jo
Most of the previous work on non-invasive brain-computer interfaces (BCIs) has been focused on feature extraction and classification algorithms to achieve high performance for the communication between the brain and the computer. While significant progress has been made in the lower layer of the BCI system, the issues in the higher layer have not been sufficiently addressed. Existing P300-based BCI systems, for example the P300 speller, use a random order of stimulus sequence for eliciting P300 signal for identifying users' intentions. This paper is about computing an optimal sequence of stimulus in order to minimize the number of stimuli, hence improving the performance. To accomplish this, we model the problem as a partially observable Markov decision process (POMDP), which is a model for planning in partially observable stochastic environments. Through simulation and human subject experiments, we show that our approach achieves a significant performance improvement in terms of the success rate and the bit rate.
Keywords: P300, brain-computer interface (bci), partially observable markov decision process (pomdp)
Automatically identifying targets users interact with during real world tasks BIBAKFull-Text 11-20
  Amy Hurst; Scott E. Hudson; Jennifer Mankoff
Information about the location and size of the targets that users interact with in real world settings can enable new innovations in human performance assessment and soft-ware usability analysis. Accessibility APIs provide some information about the size and location of targets. How-ever this information is incomplete because it does not sup-port all targets found in modern interfaces and the reported sizes can be inaccurate. These accessibility APIs access the size and location of targets through low-level hooks to the operating system or an application. We have developed an alternative solution for target identification that leverages visual affordances in the interface, and the visual cues produced as users interact with targets. We have used our novel target identification technique in a hybrid solution that combines machine learning, computer vision, and accessibility API data to find the size and location of targets users select with 89% accuracy. Our hybrid approach is superior to the performance of the accessibility API alone: in our dataset of 1355 targets covering 8 popular applications, only 74% of the targets were correctly identified by the API alone.
Keywords: computer accessibility, pointing input, target identification, usability analysis
Addressing the problems of data-centric physiology-affect relations modeling BIBAKFull-Text 21-30
  Roberto Legaspi; Ken-ichi Fukui; Koichi Moriyama; Satoshi Kurihara; Masayuki Numao; Merlin Suarez
Data-centric affect modeling may render itself restrictive in practical applications for three reasons, namely, it falls short of feature optimization, infers discrete affect classes, and deals with relatively small to average sized datasets. Though it seems practical to use the feature combinations already associated to commonly investigated sensors, there may be other potentially optimal features that can lead to new relations. Secondly, although it seems more realistic to view affect as continuous, it requires using continuous labels that will increase the difficulty of modeling. Lastly, although a large scale dataset reflects a more precise range of values for any given feature, it severely hinders computational efficiency. We address these problems when inferring physiology-affect relations from datasets that contain 2-3 million feature vectors, each with 49 features and labelled with continuous affect values. We employ automatic feature selection to acquire near optimal feature subsets and a fast approximate kNN algorithm to solve the regression problem and cope with the challenge of a large scale dataset. Our results show that high estimation accuracy may be achieved even when the selected feature subset is only about 7% of the original features. May the results here motivate the HCI community to pursue affect modeling without being deterred by large datasets and further the discussions on acquiring optimal features for accurate continuous affect approximation.
Keywords: affective computing, machine learning, pattern recognition

Smart reading

Personalized news recommendation based on click behavior BIBAKFull-Text 31-40
  Jiahui Liu; Peter Dolan; Elin Rønby Pedersen
Online news reading has become very popular as the web provides access to news articles from millions of sources around the world. A key challenge of news websites is to help users find the articles that are interesting to read. In this paper, we present our research on developing personalized news recommendation system in Google News. For users who are logged in and have explicitly enabled web history, the recommendation system builds profiles of users' news interests based on their past click behavior. To understand how users' news interests change over time, we first conducted a large-scale analysis of anonymized Google News users click logs. Based on the log analysis, we developed a Bayesian framework for predicting users' current news interests from the activities of that particular user and the news trends demonstrated in the activity of all users. We combine the content-based recommendation mechanism which uses learned user profiles with an existing collaborative filtering mechanism to generate personalized news recommendations. The hybrid recommender system was deployed in Google News. Experiments on the live traffic of Google News website demonstrated that the hybrid method improves the quality of news recommendation and increases traffic to the site.
Keywords: news trend, personalization, user modeling
Aspect-level news browsing: understanding news events from multiple viewpoints BIBAKFull-Text 41-50
  Souneil Park; SangJeong Lee; Junehwa Song
Aspect-level news browsing provides readers with a classified view of news articles with different viewpoints. It facilitates active interactions with which readers easily discover and compare diverse existing biased views over a news event. As such, it effectively helps readers understand the event from a plural of viewpoints and formulate their own, more balanced viewpoints free from specific biased views. Realizing aspect-level browsing raises important challenges, mainly due to the lack of semantic knowledge with which to abstract and classify the intended salient aspects of articles. We first demonstrate the feasibility of aspect-level news browsing through user studies. We then deeply look into the news article production process and develop framing cycle-aware clustering. The evaluation results show that the developed method performs classification more accurately than other methods.
Keywords: aspect-level classification, aspect-level news browsing, media bias
Personalized reading support for second-language web documents by collective intelligence BIBAKFull-Text 51-60
  Yo Ehara; Nobuyuki Shimizu; Takashi Ninomiya; Hiroshi Nakagawa
Novel intelligent interface eases the browsing of Web documents written in the second languages of users. It automatically predicts words unfamiliar to the user by collective intelligence and glosses them with their meaning in advance. If the prediction succeeds, the user does not need to consult a dictionary; even if it fails, the user can correct the prediction. The correction data are collected and used to improve the accuracy of further predictions. The prediction is personalized in that every user's language ability is estimated by a state-of-the-art language testing model, which is trained in a practical response time with only a small sacrifice of prediction accuracy. Evaluation results for the system in terms of prediction accuracy are encouraging.
Keywords: collective intelligence, glossing system, item response theory, reading support, web page

Intelligent agent

Agent-assisted task management that reduces email overload BIBAKFull-Text 61-70
  Andrew Faulring; Brad Myers; Ken Mohnkern; Bradley Schmerl; Aaron Steinfeld; John Zimmerman; Asim Smailagic; Jeffery Hansen; Daniel Siewiorek
RADAR is a multiagent system with a mixed-initiative user interface designed to help office workers cope with email overload. RADAR agents observe experts to learn models of their strategies and then use the models to assist other people who are working on similar tasks. The agents' assistance helps a person to transition from the normal email-centric workflow to a more efficient task-centric workflow. The Email Classifier learns to identify tasks contained within emails and then inspects new emails for similar tasks. A novel task-management user interface displays the found tasks in a to-do list, which has integrated support for performing the tasks. The Multitask Coordination Assistant learns a model of the order in which experts perform tasks and then suggests a schedule to other people who are working on similar tasks. A novel Progress Bar displays the suggested schedule of incomplete tasks as well as the completed tasks. A large evaluation demonstrated that novice users confronted with an email overload test performed significantly better (a 37% better overall score with a factor of four fewer errors) when assisted by the RADAR agents.
Keywords: agents, email classification, email overload, intelligent planning, learning, radar, task management
An adaptive calendar assistant using pattern mining for user preference modelling BIBAKFull-Text 71-80
  Alfred Krzywicki; Wayne Wobcke; Anna Wong
In this paper, we present SmartCal, a calendar assistant that suggests appointment attributes, such as time, day, duration, etc., given any combination of initial user input attributes. SmartCal uses closed pattern mining to discover patterns in past appointment data in order to represent user preferences and adapt to changing user preferences over time. The SmartCal interface is designed to be minimally intrusive: users are free to choose or ignore suggestions, which are dynamically updated as users enter new information. The user model as a collection of patterns is intuitive and transparent: users can view and edit existing patterns or create new patterns based on existing appointments. SmartCal was evaluated in a user study with four users over a four week period. The user study shows that pattern mining makes appointment creation more efficient and users regarded the appointment suggestion feature favourably.
Keywords: calendar management, data mining, personal assistants
Tell me more, not just "more of the same" BIBAKFull-Text 81-90
  Francisco Iacobelli; Larry Birnbaum; Kristian J. Hammond
The Web makes it possible for news readers to learn more about virtually any story that interests them. Media outlets and search engines typically augment their information with links to similar stories. It is up to the user to determine what new information is added by them, if any. In this paper we present Tell Me More, a system that performs this task automatically: given a seed news story, it mines the web for similar stories reported by different sources and selects snippets of text from those stories which offer new information beyond the seed story. New content may be classified as supplying: additional quotes, additional actors, additional figures and additional information depending on the criteria used to select it. In this paper we describe how the system identifies new and informative content with respect to a news story. We also how that providing an explicit categorization of new information is more useful than a binary classification (new/not-new). Lastly, we show encouraging results from a preliminary evaluation of the system that validates our approach and encourages further study.
Keywords: dimensions of similarity, information retrieval, new information detection

Mobile interaction

Rush: repeated recommendations on mobile devices BIBAKFull-Text 91-100
  Dominikus Baur; Sebastian Boring; Andreas Butz
We present rush as a recommendation-based interaction and visualization technique for repeated item selection from large data sets on mobile touch screen devices. Proposals and choices are intertwined in a continuous finger gesture navigating a two-dimensional canvas of recommended items. This provides users with more flexibility for the resulting selections. Our design is based on a formative user study regarding orientation and occlusion aspects. Subsequently, we implemented a version of rush for music playlist creation. In an experimental evaluation we compared different types of recommendations based on similarity, namely the top 5 most similar items, five random selections from the list of similar items and a hybrid version of the two. Participants had to create playlists using each condition. Our results show that top 5 was too restricting, while random and hybrid suggestions had comparable results.
Keywords: interaction technique, mobile, recommender systems
SocialSearchBrowser: a novel mobile search and information discovery tool BIBAKFull-Text 101-110
  Karen Church; Joachim Neumann; Mauro Cherubini; Nuria Oliver
The mobile Internet offers anytime, anywhere access to a wealth of information to billions of users across the globe. However, the mobile Internet represents a challenging information access platform due to the inherent limitations of mobile environments, limitations that go beyond simple screen size and network issues. Mobile users often have information needs which are impacted by contexts such as location and time. Furthermore, human beings are social creatures that often seek out new strategies for sharing knowledge and information in mobile settings. To investigate the social aspect of mobile search, we have developed SocialSearchBrowser (SSB), a novel proof-of-concept interface that incorporates social networking capabilities with key mobile contexts to improve the search and information discovery experience of mobile users. In this paper, we present the results of an exploratory field study of SSB and outline key implications for the design of next generation mobile information access services.
Keywords: context, field study, location-based services, mobile search, social networks, social search, user evaluation
Usability guided key-target resizing for soft keyboards BIBAKFull-Text 111-118
  Asela Gunawardana; Tim Paek; Christopher Meek
Soft keyboards offer touch-capable mobile and tabletop devices many advantages such as multiple language support and room for larger displays. On the other hand, because soft keyboards lack haptic feedback, users often produce more typing errors. In order to make soft keyboards more robust to noisy input, researchers have developed key-target resizing algorithms, where underlying target areas for keys are dynamically resized based on their probabilities. In this paper, we describe how overly aggressive key-target resizing can sometimes prevent users from typing their desired text, violating basic user expectations about keyboard functionality. We propose an anchored key-target method which incorporates usability principles so that soft keyboards can remain robust to errors while respecting usability principles. In an empirical evaluation, we found that using anchored dynamic key-targets significantly reduce keystroke errors as compared to the state-of-the-art.
Keywords: language model, source-channel key-target resizing, touch model

Multimodal interaction

Intelligent understanding of handwritten geometry theorem proving BIBAKFull-Text 119-128
  Yingying Jiang; Feng Tian; Hongan Wang; Xiaolong Zhang; Xugang Wang; Guozhong Dai
Computer-based geometry systems have been widely used for teaching and learning, but largely based on mouse-and-keyboard interaction, these systems usually require users to draw figures by following strict task structures defined by menus, buttons, and mouse and keyboard actions. Pen-based designs offer a more natural way to develop geometry theorem proofs with hand-drawn figures and scripts. This paper describes a pen-based geometry theorem proving system that can effectively recognize hand-drawn figures and hand-written proof scripts, and accurately establish the correspondence between geometric components and proof steps. Our system provides dynamic and intelligent visual assistance to help users understand the process of proving and allows users to manipulate geometric components and proof scripts based on structures rather than strokes. The results from evaluation study show that our system is well perceived and users have high satisfaction with the accuracy of sketch recognition, the effectiveness of visual hints, and the efficiency of structure-based manipulation.
Keywords: geometry theorem proving, hand-drawn figures, hand-written proof scripts, recognition, structure based manipulation
Usage patterns and latent semantic analyses for task goal inference of multimodal user interactions BIBAKFull-Text 129-138
  Pui-Yu Hui; Wai-Kit Lo; Helen Meng
This paper describes our work in usage pattern analysis and development of a latent semantic analysis framework for interpreting multimodal user input consisting speech and pen gestures. We have designed and collected a multimodal corpus of navigational inquiries. Each modality carries semantics related to domain-specific task goal. Each inquiry is annotated manually with a task goal based on the semantics. Multimodal input usually has a simpler syntactic structure than unimodal input and the order of semantic constituents is different in multimodal and unimodal inputs. Therefore, we proposed to use semantic analysis to derive the latent semantics from the multimodal inputs using latent semantic modeling (LSM). In order to achieve this, we parse the recognized Chinese spoken input for the spoken locative references (SLR). These SLRs are then aligned with their corresponding pen gesture(s). Then, we characterized the cross-modal integration pattern as 3-tuple multimodal terms with SLR, pen gesture type and their temporal relation. The inquiry-multimodal term matrix is then decomposed using singular value decomposition (SVD) to derive the latent semantics automatically. Task goal inference based on the latent semantics shows that the task goal inference accuracy on a disjoint test set is of 99%.
Keywords: latent semantic modeling, multimodal input, pen gesture, singular value decomposition, spoken input, task goal inference
Estimating user's engagement from eye-gaze behaviors in human-agent conversations BIBAKFull-Text 139-148
  Yukiko I. Nakano; Ryo Ishii
In face-to-face conversations, speakers are continuously checking whether the listener is engaged in the conversation and change the conversational strategy if the listener is not fully engaged in the conversation. With the goal of building a conversational agent that can adaptively control conversations with the user, this study analyzes the user's gaze behaviors and proposes a method for estimating whether the user is engaged in the conversation based on gaze transition 3-gram patterns. First, we conduct a Wizard-of-Oz experiment to collect the user's gaze behaviors. Based on the analysis of the gaze data, we propose an engagement estimation method that detects the user's disengagement gaze patterns. The algorithm is implemented as a real-time engagement-judgment mechanism and is incorporated into a multimodal dialogue manager in a conversational agent. The agent estimates the user's conversational engagement and generates probing questions when the user is distracted from the conversation. Finally, we conduct an evaluation experiment using the proposed engagement-sensitive agent and demonstrate that the engagement estimation function improves the user's impression of the agent and the interaction with the agent. In addition, probing performed with proper timing was also found to have a positive effect on user's verbal/nonverbal behaviors in communication with the conversational agent.
Keywords: conversational agent, conversational engagement, dialogue management, eye-gaze

Smart web apps

Embedded media markers: marks on paper that signify associated media BIBAKFull-Text 149-158
  Qiong Liu; Chunyuan Liao; Lynn Wilcox; Anthony Dunnigan; Bee Liew
Embedded Media Markers, or simply EMMs, are nearly transparent iconic marks printed on paper documents that signify the existence of media associated with that part of the document. EMMs also guide users' camera operations for media retrieval. Users take a picture of an EMM-signified document patch using a cell phone, and the media associated with the EMM-signified document location is displayed on the phone. Unlike bar codes, EMMs are nearly transparent and thus do not interfere with the document appearance. Retrieval of media associated with an EMM is based on image local features of the captured EMM-signified document patch. This paper describes a technique for semi-automatically placing an EMM at a location in a document, in such a way that it encompasses sufficient identification features with minimal disturbance to the original document.
Keywords: augmented paper, barcode, camera phone, document recognition, marker on paper, vision-based paper interface
WildThumb: a web browser supporting efficient task management on wide displays BIBAKFull-Text 159-168
  Shenwei Liu; Keishi Tajima
Nowadays the Web and Web browsers have become the most important and universal platform for people to search, view, process, and exchange various kinds of information. Consequently, today's users usually open many Web pages simultaneously in order to perform multiple tasks in parallel, which makes Web browsers crucial in our daily task management. However, no existing Web browser provides users with sufficient support for the management of many tabs or windows of opened pages. On the other hand, wide displays have become more affordable and prevalent, while extra space on those displays is not utilized effectively in Web browsing. In this paper, we propose a new Web browser interface aiming to support efficient task management in Web browsing on wide displays. In order to help users switch between opened Web pages, we show thumbnails of the pages in the extra space around the currently focused page. In the page thumbnails, we emphasize distinctive elements in each page in order to make the selection of the thumbnails easier. In addition, we calculate the relevance between pages based on users' switching history, and emphasize pages relevant to the current page by adjusting the size or opacity of the thumbnails. This further helps users find the thumbnails of needed pages, and also helps users get the overview of the page set related to the current task.
Keywords: augmented thumbnail, multitask, site logo, tab-browser, task grouping, task switching, window system, working set
Lowering the barriers to website testing with CoTester BIBAKFull-Text 169-178
  Jalal Mahmud; Tessa Lau
In this paper, we present CoTester, a system designed to decrease the difficulty of testing web applications. CoTester allows testers to create test scripts that are represented in an easy-to-understand scripting language rather than a complex programming language, which allows tests to be created rapidly and by non-developers. CoTester improves the management of test scripts by grouping sequences of lowlevel actions into subroutines, such as "log in" or "check out shopping cart", which help testers visualize test structure and make bulk modifications. A key innovation in CoTester is its ability to automatically identify these subroutines using a machine learning algorithm. Our algorithm is able to achieve 91% accuracy at recognizing a set of 7 representative subroutines commonly found in test scripts.
Keywords: instruction, subroutine, test script, website testing

Enhanced search

Towards a reputation-based model of social web search BIBAKFull-Text 179-188
  Kevin KcNally; Michael P. O'Mahony; Barry Smyth; Maurice Coyle; Peter Briggs
While web search tasks are often inherently collaborative in nature, many search engines do not explicitly support collaboration during search. In this paper, we describe HeyStaks (www.heystaks.com), a system that provides a novel approach to collaborative web search. Designed to work with mainstream search engines such as Google, HeyStaks supports searchers by harnessing the experiences of others as the basis for result recommendations. Moreover, a key contribution of our work is to propose a reputation system for HeyStaks to model the value of individual searchers from a result recommendation perspective. In particular, we propose an algorithm to calculate reputation directly from user search activity and we provide encouraging results for our approach based on a preliminary analysis of user activity and reputation scores across a sample of HeyStaks users.
Keywords: collaborative web search, heystaks, reputation model
DocuBrowse: faceted searching, browsing, and recommendations in an enterprise context BIBAKFull-Text 189-198
  Andreas Girgensohn; Frank Shipman; Francine Chen; Lynn Wilcox
Browsing and searching for documents in large, online enterprise document repositories are common activities. While internet search produces satisfying results for most user queries, enterprise search has not been as successful because of differences in document types and user requirements. To support users in finding the information they need in their online enterprise repository, we created DocuBrowse, a faceted document browsing and search system. Search results are presented within the user-created document hierarchy, showing only directories and documents matching selected facets and containing text query terms. In addition to file properties such as date and file size, automatically detected document types, or genres, serve as one of the search facets. Highlighting draws the user's attention to the most promising directories and documents while thumbnail images and automatically identified keyphrases help select appropriate documents. DocuBrowse utilizes document similarities, browsing histories, and recommender system techniques to suggest additional promising documents for the current facet and content filters.
Keywords: document management, document recommendation, document retrieval, document visualization, faceted search
Facilitating exploratory search by model-based navigational cues BIBAKFull-Text 199-208
  Wai-Tat Fu; Thomas G. Kannampallil; Ruogu Kang
We present an extension of a computational cognitive model of social tagging and exploratory search called the semantic imitation model. The model assumes a probabilistic representation of semantics for both internal and external knowledge, and utilizes social tags as navigational cues during exploratory search. We used the model to generate a measure of information scent that controls exploratory search behavior, and simulated the effects of multiple presentations of navigational cues on both simple information retrieval and exploratory search performance based on a previous model called SNIF-ACT. We found that search performance can be significantly improved by these model-based presentations of navigational cues for both experts and novices. The result suggested that exploratory search performance depends critically on the match between internal knowledge (domain expertise) and external knowledge structures (folksonomies). Results have significant implications on how social information systems should be designed to facilitate knowledge exchange among users with different background knowledge.
Keywords: exploratory learning, knowledge exchange, semantic imitation, snif-act, social tagging
Outline wizard: presentation composition and search BIBAKFull-Text 209-218
  Lawrence Bergman; Jie Lu; Ravi Konuru; Julie MacNaught; Danny Yeh
Presentation material is a commonly-performed task. Yet current tools provide inadequate support -- search tools are unable to return individual slides, and the linear model employed by presentation creation tools lacks structure and context. We propose a novel method for presentation creation, implemented in a tool called Outline Wizard, which enables outline-based composition and search. An Outline Wizard user enters a hierarchically-structured outline of a presentation; using that structure, the tool extracts user requests to formulate contextual queries, matches them against presentations within a repository, taking into account both content and structures of the presentations, and presents the user with sets of slides that are appropriate for each outline topic. At the heart of Outline Wizard is an outline-based search technique, which conducts content search within the context derived from the hierarchical structures of both user requests and presentations. We present a heuristic outline-extraction technique, which is used to reverse engineer the structures of presentations, thereby making the structures available for our search engine. Evaluations show that the outline extraction technique and outline-based search both perform well, and that users report a satisfying experience when using Outline Wizard to compose presentations from libraries of existing material.
Keywords: context-sensitive information retrieval, outline-based search, presentation composition, presentation search

UI for the masses

A code reuse interface for non-programmer middle school students BIBAKFull-Text 219-228
  Paul A. Gross; Micah S. Herstand; Jordana W. Hodges; Caitlin L. Kelleher
We describe a code reuse tool for use in the Looking Glass IDE, the successor to Storytelling Alice [17], which enables middle school students with little to no programming experience to reuse functionality they find in programs written by others. Users (1) record a feature to reuse, (2) find code responsible for the feature, (3) abstract the code into a reusable Actionscript by describing object "roles," and (4) integrate the Actionscript into another program. An exploratory study with middle school students indicates they can successfully reuse code. Further, 36 of the 47 users appropriated new programming constructs through the process of reuse.
Keywords: code reuse, end user, looking glass, middle school, non-programmer, storytelling alice
Speeding pointing in tiled widgets: understanding the effects of target expansion and misprediction BIBAKFull-Text 229-238
  Jaime Ruiz; Edward Lank
Target expansion is a pointing facilitation technique where the user's target, typically an interface widget, is dynamically enlarged to speed pointing in interfaces. However, with densely packed (tiled) arrangements of widgets, interfaces cannot expand all potential targets; they must, instead, predict the user's desired target. As a result, mispredictions will occur which may disrupt the pointing task. In this paper, we present a model describing the cost/benefit of expanding multiple targets using the probability distribution of a given predictor. Using our model, we demonstrate how the model can be used to infer the accuracy required by target prediction techniques. The results of this work are another step toward pointing facilitation techniques that allow users to outperform Fitts' Law in realistic pointing tasks.
Keywords: Fitts' law, human performance, pointing, target expansion, tiled targets

User-centered design

Local danger warnings for drivers: the effect of modality and level of assistance on driver reaction BIBAKFull-Text 239-248
  Yujia Cao; Angela Mahr; Sandro Castronovo; Mariët Theune; Christoph Stahl; Christian A. Müller
Local danger warning is an important function of Advanced Driver Assistance Systems (ADAS) to improve the safety of driving. The user interface (the warning presentation) is particularly crucial to a successful danger avoidance. We present a user study investigating various warning presentations using a scenario of emergent road obstacles. Two presentation factors were selected: modality and level of assistance. The modality factor had 4 variants: speech warning, visual and speech warning, visual warning with blinking cue, and visual warning with sound cue. The level of assistance varied between with or without action suggestions (AS). In accordance with the ISO usability model, a total of 6 measurements were derived to assess the effectiveness and efficiency of the warnings and the drivers' satisfaction. Results indicate that the combination of speech and visual modality leads to the best performance as well as the highest satisfaction. In contrast, purely auditory and purely visual modalities were both insufficient for presenting high-priority warnings. AS generally improved the usability of the warnings especially when they were accompanied by supporting information so that drivers could validate the suggestions.
Keywords: automotive, car2car communication, multimodal interfaces
Designing a thesaurus-based comparison search interface for linked cultural heritage sources BIBAKFull-Text 249-258
  Alia Amin; Michiel Hildebrand; Jacco van Ossenbruggen; Lynda Hardman
Comparison search is an information seeking task where a user examines individual items or sets of items for similarities and differences. While this is a known information need among experts and knowledge workers, appropriate tools are not available. In this paper, we discuss comparison search in the cultural heritage domain, a domain characterized by large, rich and heterogeneous data sets, where different organizations deploy different schemata and terminologies to describe their artifacts. This diversity makes meaningful comparison difficult. We developed a thesaurus-based comparison search application called LISA, a tool that allows a user to search, select and compare sets of artifacts. Different visualizations allow users to use different comparison strategies to cope with the underlying heterogeneous data and the complexity of the search tasks. We conducted two user studies. A preliminary study identifies the problems experts face while performing comparison search tasks. A second user study examines the effectiveness of LISA in helping to solve comparison search tasks. The main contribution of this paper is to establish design guidelines for the data and interface of a comparison search application. Moreover, we offer insights into when thesauri and metadata are appropriate for use in such applications.
Keywords: comparison search, cultural heritage, thesauri
Towards maximizing the accuracy of human-labeled sensor data BIBAKFull-Text 259-268
  Stephanie L. Rosenthal; Anind K. Dey
We present two studies that evaluate the accuracy of human responses to an intelligent agent's data classification questions. Prior work has shown that agents can elicit accurate human responses, but the applications vary widely in the data features and prediction information they provide to the labelers when asking for help. In an initial analysis of this work, we found the five most popular features, namely uncertainty, amount and level of context, prediction of an answer, and request for user feedback. We propose that there is a set of these data features and prediction information that maximizes the accuracy of labeler responses. In our first study, we compare accuracy of users of an activity recognizer labeling their own data across the dimensions. In the second study, participants were asked to classify a stranger's emails into folders and strangers' work activities by interruptibility. We compared the accuracy of the responses to the users' self-reports across the same five dimensions. We found very similar combinations of information (for users and strangers) that led to very accurate responses as well as more feedback that the agents could use to refine their predictions. We use these results for insight into the information that help labelers the most.
Keywords: active learning, labeling sensor data

Short paper presentations (posters)

Mobia Modeler: easing the creation process of mobile applications for non-technical users BIBAKFull-Text 269-272
  Florence Balagtas-Fernandez; Max Tafelmayer; Heinrich Hussmann
The development of mobile applications has now extended from mobile network providers into the hands of ordinary people as organizations and companies encourage people to come up with their own software masterpieces by opening up APIs and tools. However, as of the moment, these APIs and tools are only usable by people with programming skills. There is a scarcity of tools that enable users without programming experience to easily build customized mobile applications. We present in this paper a tool and its underlying framework that would enable non-technical people to create their own domain-specific mobile applications. As a proof of concept, we focus on the creation of applications in the domain of mobile health monitoring. In the future, we would like to extend our work to cover other domains as well.
Keywords: domain-specific modeling, mobile application, modeling tools, user-centered design
Activity interface for physical activity motivating games BIBAKFull-Text 273-276
  Shlomo Berkovsky; Mac Coombe; Richard Helmer
Contemporary lifestyle is becoming increasingly sedentary with no or little physical activity. We propose a novel design for physical activity motivating games that leverages engagement with games in order to motivate users to perform physical activity as part of traditionally sedentary playing. This paper focuses on the wearable activity interface for physical activity motivating games. We discuss the activity interface design considerations, present physical activity processing details, and analyse some observations of user interaction with the activity interface.
Keywords: physical activity, serious games, wearable interface
Evaluating the design of inclusive interfaces by simulation BIBAKFull-Text 277-280
  Pradipta Biswas; Peter Robinson
We have developed a simulator to help with the design and evaluation of assistive interfaces. The simulator can predict possible interaction patterns when undertaking a task using a variety of input devices, and estimate the time to complete the task in the presence of different dis-abilities. In this paper, we have presented a study to evaluate the simulator by considering a representative application being used by able-bodied, visually impaired and mobility impaired people. The simulator predicted task completion times for all three groups with statistically significant accuracy. The simulator also predicted the effects of different interface designs on task completion time accurately.
Keywords: assistive technology, human computer interaction, simulator, usability evaluation, user model
Temporal task footprinting: identifying routine tasks by their temporal patterns BIBAKFull-Text 281-284
  Oliver Brdiczka; Norman Makoto Su; James Bo Begole
This paper introduces a new representation for describing routine tasks, called temporal task footprints. Routines are characterized by their temporal regularity or rhythm. Temporal pattern analysis (T-patterns) can be used to isolate frequent recurrent patterns in routine tasks that appear repeatedly in the same temporal configuration. Using tf-idf statistics, each task can then be defined in terms of its temporal task footprint, a ranked list of temporal patterns along with their typical frequencies. Experimental evaluations using data of 29 days observing and logging 10 subjects showed that temporal task footprints of application windows, email and document usage outperform decision tree and SVMs in recognizing the subjects' tasks.
Keywords: routine task representation, t-patterns, task footprint, temporal patterns
From documents to tasks: deriving user tasks from document usage patterns BIBAKFull-Text 285-288
  Oliver Brdiczka
A typical knowledge worker is involved in multiple tasks and switches frequently between them every work day. These frequent switches become expensive because each task switch requires some recovery time as well as the reconstitution of task context. First task management support systems have been proposed in recent years in order to assist the user during these switches. However, these systems still need a fairly big amount of investment from the user side in order to either learn to use or train such a system. In order to reduce the necessary amount of training, this paper proposes a new approach for automatically estimating a user's tasks from document interactions in an unsupervised manner. While most previous approaches to task detection look at the content of documents or window titles, which might raise confidentiality and privacy issues, our approach only requires document identifiers and the temporal switch history between them as input. Our prototype system monitors a user's desktop activities and logs documents that have focus on the user's desktop by attributing a unique identifier to each of these documents. Retrieved documents are filtered by their dwell times and a document similarity matrix is estimated based on document frequencies and switches. A spectral clustering algorithm then groups documents into tasks using the derived similarity matrix. The described prototype system has been evaluated on user data of 29 days from 10 different subjects in a corporation. Obtained results indicate that the approach is better than previous approaches that use content.
Keywords: automatic task identification, document clustering, user task modeling
Towards intelligent motion inferencing in mathematical sketching BIBAKFull-Text 289-292
  Salman Cheema; Joseph J., Jr. LaViola
We present a new approach for creating dynamic illustrations to assist in the understanding of concepts in physics and mathematics using pen-based interaction. Our approach builds upon mathematical sketching by combining the ability to make associations between handwritten mathematics and free-form drawings with an underlying physics engine. This combination lets users create animations without having to directly specify object behavior with position functions through time, yet still supports writing the mathematics needed to formulate a problem. This functionality significantly expands the capabilities of mathematical sketching to support a wider variety of dynamic illustrations. We describe our approach to creating this mathematical sketching/physics engine fusion and discuss how it provides a foundation for using mathematical sketching in intelligent tutoring systems.
Keywords: mathematical sketching, pen-based interfaces, sketch inferencing, sketch parsing
iSlideShow: a content-aware slideshow system BIBAKFull-Text 293-296
  Jiajian Chen; Jun Xiao; Yuli Gao
We present an intelligent photo slideshow system that automatically analyzes thematic information about the photo collection and utilizes such information to generate compositions and transitions in two modes: story-telling mode and person-highlighting mode. In the story-telling mode the system groups photos by a theme-based clustering algorithm and multiple photos in each theme cluster are seamlessly tiled on a slide. Multiple tiling layouts are generated for each theme cluster and the slideshow is animated by intra-cluster transitions. In the person-highlighting mode, the system first recognizes faces from photos and creates photo clusters for individuals. It then uses face areas as ROI (Regions of Interests) and creates various content-based transitions to highlight individuals in a cluster. With an emphasis on photo content, our system creates slideshows with more fluid, dynamic and meaningful structure compared to existing systems.
Keywords: GPU, content-based transition, slideshow, theme clustering
Social influence of product popularity on consumer decisions: usability study of Flickr camera finder BIBAKFull-Text 297-300
  Li Chen
"Product popularity" is in-depth explored in this paper, regarding its practical role within a consumer's decision process. Specifically, the usability evaluation of a novel product finder service (Flickr Camera Finder) shows that users more frequently consulted it, rather than a standard shopping site, to locate popular products. User comments further revealed their credibility concerns and tendency to trust the "popularity" from social resources. Design implications from the experiment are summarized at the end, indicating suggestive directions to integrate social media data to boost current e-commerce decision tools.
Keywords: Flickr camera finder, consumer decision behavior, e-commerce, product popularity, social influence, usability study
Raconteur: from intent to stories BIBAKFull-Text 301-304
  Pei-Yu Chi; Henry Lieberman
When editing a story from a large collection of media, such as photos and video clips captured from daily life, it is not always easy to understand how particular scenes fit into the intent for the overall story. Especially for novice editors, there is often a lack of coherent connections between scenes, making it difficult for the viewers to follow the story.
   In this paper, we present Raconteur, a story editing system that helps users assemble coherent stories from media elements, each annotated with a sentence or two in unrestricted natural language. It uses a Commonsense knowledge base, and the AnalogySpace Commonsense reasoning technique. Raconteur focuses on finding story analogies -- different elements illustrating the same overall "point", or independent stories exhibiting similar narrative structures.
Keywords: commonsense computing, media editing, photograph, story analogy, story goal, storytelling, video
Error-tolerant version space algebra BIBAKFull-Text 305-308
  Eugene R. Creswick; Aaron M. Novstrup
Application customization has been extensively researched in the field of Programming by Demonstration (PBD), and Version Space Algebra has proven itself to be a viable means of quickly learning precise action sequences from user demonstrations. However, this technique is not capable of handling user error in domains with actions that depend on parameters that accept myriad values. Activities such as image, audio and video editing require user actions that are difficult for users to precisely replicate in different circumstances. Demonstrations that are off by a single pixel or a split-second cause traditional composite Version Spaces to collapse.
   We present a method of incorporating error tolerance into Version Space algebra. This approach, termed Error-Tolerant Version Spaces, adapts Version Space Algebra to domains where the tactile capabilities of the user have a much greater chance of prematurely collapsing the hypothesis space that is being learned. The resulting framework is capable of quickly learning in domains where perfectly consistent user input can not be expected. We have successfully applied our technique in the domain of image redaction, allowing our users to quickly specify redactions that can be reliably applied to many images without the entry of explicit parameters.
Keywords: error tolerance, programming by demonstration, smart environments, version spaces
Social signal processing: detecting small group interaction in leisure activity BIBAKFull-Text 309-312
  Eyal Dim; Tsvi Kuflik
Social Signal Processing of small groups enables detection of their social context. Monitoring of the social context may be based on position proximity (as a pre-condition for conversation), and on voice communication (an evidence for interaction). Understanding of the social context of a group may allow a system to intervene at the right moment and to suggest relevant services/information. This, in turn, may enhance the group members' experience during leisure activity. This study focuses on assessing the possibility of automatic detection of intra group interaction in a museum environment. It presents analysis and tools that intend to set the foundation for computer aided group interaction during leisure activities.
Keywords: group modeling, interrupt management, social signal processing, ubiquitous computing
Toward a cultural-sensitive image tagging interface BIBAKFull-Text 313-316
  Wei Dong; Wai-Tat Fu
Do people from different cultures tag digital images differently? The current study examined the relationship between the position and content of tags for digital images created by participants from two cultural groups (European Americans and Chinese). In line with previous findings on cultural differences in attentional patterns, we found cultural differences in the order of the parts of images people chose to tag. European Americans tended to tag main objects first, and tag background objects and overall properties in the images later; in contrast, Chinese tended to tag the overall properties first, and tag the main and background objects later. Based on findings of the current study, we discuss implications on developing a cultural-sensitive algorithm to facilitate the tagging and search process of digital media and data-mining tools to identify user profiles based on their cultural origins.
Keywords: algorithm, annotation, attention, cultural difference, image tagging, perception, tagging
Personalized user interfaces for product configuration BIBAKFull-Text 317-320
  Alexander Felfernig; Monika Mandl; Juha Tiihonen; Monika Schubert; Gerhard Leitner
Configuration technologies are well established as a foundation of mass customization which is a production paradigm that supports the manufacturing of highly-variant products under pricing conditions similar to mass production. A side-effect of the high diversity of products offered by a configurator is that the complexity of the alternatives may outstrip a user's capability to explore them and make a buying decision. In order to improve the quality of configuration processes, we combine knowledge-based configuration with collaborative and content-based recommendation algorithms. In this paper we present configuration techniques that recommend personalized default values to users. Results of an empirical study show improvements in terms of, for example, user satisfaction or the quality of the configuration process.
Keywords: configuration systems, model-based diagnosis, recommender systems
Intelligent food planning: personalized recipe recommendation BIBAKFull-Text 321-324
  Jill Freyne; Shlomo Berkovsky
As the obesity epidemic takes hold across the world many medical professionals are referring users to online systems aimed at educating and persuading users to alter their lifestyle. The challenge for many of these systems is to increase initial adoption and sustain participation for sufficient time to have real impact on the life of its users. In this work we present some preliminary investigation into the design of a recipe recommender, aimed at educating and sustaining user participation, which makes tailored recommendations of healthy recipes. We concentrate on the two initial dimensions of food recommendations: data capture and food-recipe relationships and present a study into the suitability of varying recommender algorithms for the recommendation of recipes.
Keywords: collaborative filtering, food, personalization, recipe, recommender systems
A natural language interface of thorough coverage by concordance with knowledge bases BIBAKFull-Text 325-328
  Yong-Jin Han; Tae-Gil Noh; Seong-Bae Park; Se Young Park; Sang-Jo Lee
One of the critical problems in natural language interfaces is the discordance between the expressions covered by the interface and those by the knowledge base. In the graph-based knowledge base such as an ontology, all possible queries can be prepared in advance. As a solution of the discordance problem in natural language interfaces, this paper proposes a method that translates a natural language query into a formal language query such as SPARQL. In this paper, a user query is translated into a formal language by choosing the most appropriate query from the prepared queries. The experimental results show a high accuracy and coverage for the given knowledge base.
Keywords: knowledge base, knowledge concordance, natural language interface, ontology
Exploratory information search by domain experts and novices BIBAKFull-Text 329-332
  Ruogu Kang; Wai-Tat Fu
The arising popularity of social tagging system has the potential to transform traditional web search into a new era of social search. Based on the finding that domain expertise could influence search behavior in traditional search engines, we hypothesized and tested the idea that domain expertise would have similar influence on search behavior in a social tagging system. We conducted an experiment comparing search behavior of experts and novices when they searched using a tradition search engine and a social tagging system. Results from our experiment showed that experts relied more on their own domain knowledge to generate search queries, while novices were influenced more by social cues in the social tagging system. Experts were also found to conform to each other more than novices in their choice of bookmarks and tags. Implications on the design of future social information systems are discussed.
Keywords: domain expertise, exploratory search, social search
Using language complexity to measure cognitive load for adaptive interaction design BIBAKFull-Text 333-336
  M. Asif Khawaja; Fang Chen; Nadine Marcus
An adaptive interaction system, which is aware of the users' current cognitive load, can change its response, presentation and interaction flow to improve users' experience and their task performance. In this paper, we propose a novel speech content analysis approach for measuring users' cognitive load, based on their language and dialogue complexity. We have analysed the transcribed speech of operators working in computerized incident control rooms and involved in highly complex bushfire management tasks in Australia. The resulting patterns of language complexity show significant differences between the speech from cognitively low load and high load tasks. We also discuss the value of using this approach of cognitive load measurement for user interface evaluation and interaction design improvement.
Keywords: cognitive load, interaction design, language complexity measures, measurement
Activity awareness in family-based healthy living online social networks BIBAKFull-Text 337-340
  Stephen Kimani; Shlomo Berkovsky; Greg Smith; Jill Freyne; Nilufar Baghaei; Dipak Bhandari
Social relationships and family involvement play an important role in health management, whereas activity awareness is useful in decision-making and stimulating motivation and action. In this paper, we propose a novel activity awareness user interface for family-oriented healthy living social networks. It is intended to increase family members' interaction with healthy living social networks. A user study showed that the activity awareness interface can add value to specific aspects of interaction with family-based healthy living social applications. The interface increased interaction with the underlying healthy living content and led to higher level of learning about healthy living and impact on specific healthy living activities. There was also significant appreciation of and interaction with the activity awareness user interface elements.
Keywords: activity awareness, evaluation, families, healthy living, online social networks, user interaction, user interface
A $3 gesture recognizer: simple gesture recognition for devices equipped with 3D acceleration sensors BIBAKFull-Text 341-344
  Sven Kratz; Michael Rohs
We present the $3 Gesture Recognizer, a simple but robust gesture recognition system for input devices featuring 3D acceleration sensors. The algorithm is designed to be implemented quickly in prototyping environments, is intended to be device-independent and does not require any special toolkits or frameworks. It relies solely on simple trigonometric and geometric calculations. A user evaluation of our system resulted in a correct gesture recognition rate of 80%, when using a set of 10 unique gestures for classification. Our method requires significantly less training data than other gesture recognizers and is thus suited to be deployed and to deliver results rapidly.
Keywords: 3D gestures, classifier, gesture recognition, rapid prototyping, recognition rates, user interfaces
A multimodal labeling interface for wearable computing BIBAKFull-Text 345-348
  Shanqing Li; Yunde Jia
Under wearable environments, it is not convenient to label an object with portable keyboards and mice. This paper presents a multimodal labeling interface to solve this problem with natural and efficient operations. Visual and audio modalities cooperate with each other: an object is encircled by visual tracking of a pointing gesture, and meanwhile its name is obtained by speech recognition. In this paper, we propose a concept of virtual touchpad based on stereo vision techniques. With the touchpad, the object encircling task is achieved by drawing a closed curve on a transparent blackboard. The touch events and movements of a pointing gesture are robustly detected for natural gesture interactions. The experimental results demonstrate the efficiency and usability of our multimodal interface.
Keywords: multimodal labeling, virtual touchpad, wearable computing
Avara: a system to improve user experience in web and virtual world BIBAKFull-Text 349-352
  Jalal Mahmud; Yun-Wu Huang; John Ponzo; Roger Pollak
3D virtual world software is becoming a popular medium for entertainment, social interaction and commerce. To the best of our knowledge, there is no system available to facilitate the bridging between Web applications and virtual world systems in the form of information sharing, data collection and control propagation. As a result, user experience in a Web interface is not sensitive to state changes of virtual world avatars or objects. Similarly, a virtual world environment does not provide Web context-rich user experience. We address this issue and propose a bridging and context sharing architecture between the Web and virtual world applications such that Web applications can control, monitor and collect information from artifacts in the virtual worlds, and vice versa. We also implemented this architecture using existing Web and virtual world technologies. Based on this implementation, we illustrate some novel applications and present a user study to illustrate the value of the system.
Keywords: 3D web, bridging, second life, virtual world
Supporting exploratory information seeking by epistemology-based social search BIBAKFull-Text 353-356
  Yuqing Mao; Haifeng Shen; Chengzheng Sun
Formulating proper keywords and evaluating search results are common difficulties in exploratory information seeking. Reusing and refining others' successful searches are pragmatic directions to tackle these difficulties. In this paper, we present a novel epistemology-based social search solution, where search epistemologies are effectively shared, reused, and refined by others with the same or similar search interests through novel user interfaces. We have developed a prototype system Baijia and experimental results show that an epistemology-based social search system outperforms a conventional search engine in supporting exploratory information seeking.
Keywords: epistemology-based social search, exploratory information seeking, world wide web
Ocean of information: fusing aggregate & individual dynamics for metropolitan analysis BIBAKFull-Text 357-360
  Mauro Martino; Francesco Calabrese; Giusy Di Lorenzo; Clio Andris; Liu Liang; Carlo Ratti
In this paper, we propose a tool to explore human movement dynamics in a Metropolitan Area. By analyzing a mass of individual cell phone traces, we build a Human-City Interaction System for understanding urban mobility patterns at different user-controlled temporal and geographic scales. We solve the problems that are found in available tools for spatio-temporal analysis, by allowing seamless manipulability and introducing a simultaneous\multi-scale visualization of individual and aggregate flows. Our tool is built to support the exploration and discovery of urban mobility patterns and the daily interactions of millions of people. Moreover, we implement an intelligent algorithm to evaluate the level of mobility homophily of people moving from place to place.
Keywords: cellphone data analysis, exploratory spatial data analysis, graph visualization, intelligent human information interaction, visual analysis
Vocabulary navigation made easier BIBAKFull-Text 361-364
  Sonya Nikolova; Xiaojuan Ma; Marilyn Tremaine; Perry Cook
It is challenging to search a dictionary consisting of thousands of entries in order to select appropriate words for building written communication. This is true both for people trying to communicate in a foreign language who have not developed a full vocabulary, for school children learning to write, for authors who wish to be more precise and expressive, and especially for people with lexical access disorders. We make vocabulary navigation and word finding easier by augmenting a basic vocabulary with links between words based on human judgments of semantic similarity. In this paper, we report the results from a user study evaluating how our system named ViVA performs compared to a widely used assistive vocabulary in which words are organized hierarchically into common categories.
Keywords: adaptive user interfaces, assistive communication, semantic networks, visual vocabularies
An intuitive texture picker BIBAKFull-Text 365-368
  Wai-Man Pang
Color and texture are basic elements in digital graphics. Selection of color with a picker is convenient in many of the image editing softwares. However, more organized and intelligent GUI for texture pattern selection is still missing. In this paper, we attempt to fill this gap with the introduction of several robust techniques in building an intuitive texture picking GUI.
   By arranging patterns according to their visual similarities, texture picker with plane and circular layout are presented. Additional functionality include content-based texture searching which can quickly find similar patterns of given sample. Preliminary response to the proposed interface is positive in general, while further improvements are required, for example, on building a hierarchy to facilitate high to low level selection for huge amount of texture patterns.
Keywords: multidimensional scaling, texture pattern picker, texture selection GUI, texture similarity
Automatic generation of research trails in web history BIBAKFull-Text 369-372
  Elin Rønby Pedersen; Karl Gyllstrom; Shengyin Gu; Peter Jin Hong
We propose the concept of research trails to help web users create and reestablish context across fragmented research processes without requiring them to explicitly structure and organize the material. A research trail is an ordered sequence of web pages that were accessed as part of a larger investigation; they are automatically constructed by filtering and organizing users' activity history, using a combination of semantic and activity based criteria for grouping similar visited web pages. The design was informed by an ethnographic study of ordinary people doing research on the web, emphasizing a need to support research processes that are fragmented and where the research question is still in formation. This paper motivates and describes our algorithms for generating research trails.
   Research trails can be applied in several situations: as the underlying mechanism for a research task browser, or as feed to an ambient display of history information while searching. A prototype was built to assess the utility of the first option, a research trail browser.
Keywords: activity based computing, automatic clustering, ethnography, semantic clustering, task browser, web history
Balancing error and supervision effort in interactive-predictive handwriting recognition BIBAKFull-Text 373-376
  Nicolás Serrano; Albert Sanchis; Alfons Juan
An effective approach to transcribe handwritten text documents is to follow an interactive-predictive paradigm in which both, the system is guided by the user, and the user is assisted by the system to complete the transcription task as efficiently as possible. This approach has been recently implemented in a system prototype called GIDOC, in which standard speech technology is adapted to handwritten text (line) images: HMM-based text image modeling, n-gram language modeling, and also confidence measures on recognized words. Confidence measures are used to assist the user in locating possible transcription errors, and thus validate system output after only supervising those (few) words for which the system is not highly confident. However, a certain degree of supervision is required for proper model adaptation from partially supervised transcriptions. Here, we propose a simple yet effective method to find an optimal balance between recognition error and supervision effort.
Keywords: computer-assisted text transcription, confidence measures, document analysis, handwriting recognition
The why UI: using goal networks to improve user interfaces BIBAKFull-Text 377-380
  Dustin A. Smith; Henry Lieberman
People interact with interfaces to accomplish goals, and knowledge about human goals can be useful for building intelligent user interfaces. We suggest that modeling high, human-level goals like "repair my credit score", is especially useful for coordinating workflows between interfaces, automated planning, and building introspective applications.
   We analyzed data from 43Things.com, a website where users share and discuss goals and plans in natural language, and constructed a goal network that relates what goals people have with how people solve them. We then label goals with specific details, such as where the goal typically is met and how long it takes to achieve, facilitating plan and goal recognition. Lastly, we demonstrate a simple application of goal networks, deploying it in a mobile, location-aware to-do list application, ToDoGo, which uses goal networks to help users plan where and when to accomplish their desired goals.
Keywords: goal networks, learning goal networks, plan recognition, to-do list
A multimodal dialogue mashup for medical image semantics BIBAKFull-Text 381-384
  Daniel Sonntag; Manuel Möller
This paper presents a multimodal dialogue mashup where different users are involved in the use of different user interfaces for the annotation and retrieval of medical images. Our solution is a mashup that integrates a multimodal interface for speech-based annotation of medical images and dialogue-based image retrieval with a semantic image annotation tool for manual annotations on a desktop computer. A remote RDF repository connects the annotation and querying task into a common framework and serves as the semantic backend system for the advanced multimodal dialogue a radiologist can use.
Keywords: collaborative environments, design, touchscreen interface
Finding your way in a multi-dimensional semantic space with luminoso BIBAKFull-Text 385-388
  Robert H. Speer; Catherine Havasi; K. Nichole Treadway; Henry Lieberman
In AI, we often need to make sense of data that can be measured in many different dimensions -- thousands of dimensions or more -- especially when this data represents natural language semantics. Dimensionality reduction techniques can make this kind of data more understandable and more powerful, by projecting the data into a space of many fewer dimensions, which are suggested by the computer. Still, frequently, these results require more dimensions than the human mind can grasp at once to represent all the meaningful distinctions in the data.
   We present Luminoso, a tool that helps researchers to visualize and understand a multi-dimensional semantic space by exploring it interactively. It also streamlines the process of creating such a space, by inputting text documents and optionally including common-sense background information. This interface is based on the fundamental operation of "grabbing" a point, which simultaneously allows a user to rotate their view using that data point, view associated text and statistics, and compare it to other data points. This also highlights the point's neighborhood of semantically-associated points, providing clues for reasons as to why the points were classified along the dimensions they were. We show how this interface can be used to discover trends in a text corpus, such as free-text responses to a survey.
Keywords: common sense, n-dimensional visualization, natural language processing, svd
A multi faceted recommendation approach for explorative video retrieval tasks BIBAKFull-Text 389-392
  David Vallet; Martin Halvey; David Hannah; Joemon M. Jose
In this paper we examine the use of multi faceted recommendations to aid users while carrying out exploratory video retrieval tasks. These recommendations are integrated into ViGOR (Video Grouping, Organisation and Retrieval), a system which employs grouping techniques to facilitate video retrieval tasks. Two types of recommendations based on past usage history are utilised, the first attempts to couple the multi-faceted nature of explorative video retrieval tasks with the current user interests in order to provide global recommendations, while the second exploits the organisational features of ViGOR in order to provide recommendations based on a specific aspect of the user's task.
Keywords: collaborative, exploratory, recommendation, search, video
Evaluating automatic warning cues for visual search in vascular images BIBAKFull-Text 393-396
  Boris W. van Schooten; Betsy M. A. G. van Dijk; Anton Nijholt; Johan H. C. Reiber
Visual search is a task that is performed in various application areas. Search can be aided by an automatic warning system, which highlights the sections that may contain targets and require the user's attention. The effect of imperfect automatic warnings on overall performance ultimately depends on the interplay between the user and the automatic warning system. While various user studies exist, the different studies differ in several experimental variables including the nature of the visualisation itself. Studies in the medical area remain relatively rare, even though there is a growing interest in medical screening systems. We describe an experiment where users had to perform a visual search on a vascular structure, traversing a particular vessel linearly in search of possible errors made in an automatic segmentation. We find that only the case in which the warning system generates only false positives improves user time and error performance. We discuss this finding in relation to the findings of other studies.
Keywords: automatic warning system, image segmentation, magnetic resonance angiography, visual search
Automatic configuration of spatially consistent mouse pointer navigation in multi-display environments BIBAKFull-Text 397-400
  Manuela Waldner; Christian Pirchheim; Ernst Kruijff; Dieter Schmalstieg
Multi-display environments combine displays of various form factors into a common interaction space. Cross-display navigation techniques have to provide transitions to move the mouse pointer across display boundaries to reach distant display locations. A spatially consistent description of display relationships thereby supports fluid cross-display navigation. In this paper, we present two spatially consistent navigation techniques for seamless cross-display navigation in multi-user multi-display environments. These navigation techniques are automatically configured from a spatial model of the environment, which is generated in a camera-assisted calibration step. We describe the implementation in a distributed system and present results of a comparative experiment.
Keywords: cross-display mouse navigation, multi-display environment


User interface for filtering videos interconnecting high level and intellectual metadata BIBAKFull-Text 401-402
  Arne Berger
We present a user interface that combines the requirements needed for information search in a professional environment with the possibilities for multimedial queries based on automatically generated fuzzy high level metadata.
Keywords: filtering, interactive information retrieval, user interface
Isn't it great?: you can PLAY, MATE! BIBAKFull-Text 403-404
  Shlomo Berkovsky; Mac Coombe; Jill Freyne; Dipak Bhandari
The addictive nature of game playing contributes to an increasingly sedentary lifestyle. In this demonstration we showcase PLAY, MATE!, a novel mixed reality game design that motivates players to perform physical activity as part of playing. According to the PLAY, MATE! design, players gain virtual game rewards in return for the real physical activity they perform. We demonstrate the application of the PLAY, MATE! design to an open source game and allow participants to experience physical activity motivating games in person.
Keywords: activity motivation, bodily interface, game interaction
Understanding web documents using semantic overlays BIBAKFull-Text 405-406
  Grégoire Burel; Amparo Elizabeth Cano
The Ozone Browser is a platform independent tool that enables users to visually augment the knowledge presented in a web document in an unobtrusive way. This tool supports the user comprehension of Web documents through the use of Semantic Overlays. This tool uses linked data and lightweight semantics for getting relevant information within a document. The current implementation uses a JavaScript bookmarklet.
Keywords: semantic overlays, semantic web, web augmentation
Context-aware intelligent recommender system BIBAKFull-Text 407-408
  Mehdi Elahi
This demo paper presents a context-aware recommendation system. The system mines data from user's web searches and other sources to improve the presentation of content on visited web pages. While user is browsing the internet, a memory resident agent records and analyzes the content of the webpages that were either searched for or visited in order to identify topic preferences. Then, based on such information, the content of requested web page is ranked and classified with different styles. The demo shows how a music weblog can be modified automatically based on user's affinities.
Keywords: active learning, classification, context-aware, fuzzy logic, recommendation systems, recommenders
Mobile mentor: weight management platform BIBAKFull-Text 409-410
  Jill Freyne; Dipak Bhandari; Shlomo Berkovsky; Lyle Borlyse; Chris Campbell; Steve Chau
In recent years health care professionals have been investigating the use of ICT technologies in order to influence the general public to change their attitude and behaviour toward a healthier lifestyle. We present Mobile Mentor, a platform aimed at supporting individuals on goal driven programs through personalized mobile technology. This demonstration focuses on a weight loss prototype, Weight Management Mentor, which supports self regulation through the collection of real time diet and exercise data, self reflection and awareness through its graphical feedback mechanisms, and interaction with a health practitioner or advisor through a central server.
Keywords: diet, health, mobile
Relevant TV program retrieval using broadcast summaries BIBAKFull-Text 411-412
  Jun Goto; Hideki Sumiyoshi; Masaru Miyazaki; Hideki Tanaka; Masahiro Shibata; Akiko Aizawa
On-demand services for TV program, which provide users with past programs on demand, are becoming popular. It is therefore necessary to find a means of efficiently searching for programs that users want to view, from huge program archives. This paper proposes an automatic method of retrieving programs related to the one being viewed by the user. To that end, we compute similarity between program summaries and closed captions obtained from broadcasting by weighting significant words such as compound words and named entities. Additionally our method provides inter-program relationship labels to indicate why the results of relevant programs were chosen. The results of an evaluation showed that the method recommended relevant programs with higher accuracy than baseline methods and indicated appropriate relationship labels for related programs.
Keywords: TV program retrieval, n-gram, named entity, relationship
MagiTact: interaction with mobile devices based on compass (magnetic) sensor BIBAKFull-Text 413-414
  Hamed Ketabdar; Kamer Ali Yüksel; Mehran Roshandel
In this work, we present a new technique for efficient use of 3D space around a mobile device for interaction with the device. Around Device Interaction (ADI) enables extending interaction space of small mobile and tangible devices beyond their physical boundary. Our proposed method is based on using compass (magnetic field) sensor integrated in mobile devices (e.g. iPhone 3GS, G1 Android). In this method, a properly shaped permanent magnet (e.g. in the shape of a rod, pen or a ring) is used for interaction. The user makes coarse gestures in the 3D space around the device using the magnet. Movement of the magnet affects the magnetic field sensed by the compass sensor integrated in the device. The temporal pattern of the gesture is then used as a basis for sending different interaction commands to the mobile device. Zooming, turning pages, accepting/rejecting calls, clicking items, controlling a music player, and game interaction are some example use cases. The proposed method does not impose changes in hardware specifications of the mobile device, and unlike optical methods is not limited by occlusion problems.
Keywords: around device interaction, compass (magnetic) sensor, magnet, mobile devices, movement-based gestures
Smart ring: controlling call alert functionality based on audio and movement analysis BIBAKFull-Text 415-416
  Hamed Ketabdar; Kamer Ali Yüksel
In this work, we present a method for controlling call alert functionality in mobile phones. It has happened for almost everybody experiencing a situation that call alert functionality is not proper for actual ambient context, leading to missing a phone call or disturbing others by a loud ring. In this work, we use audio and physical movement analysis to distinguish between different situations in which a mobile phone may ring, and adjust the call alert functionality accordingly. Considering the fact that mobile phones are usually carried in a pocket or bag, capturing ambient audio is not usually practically perfect. The novelty in our work is using information about physical movements of user of mobile device in addition to analysis of ambient audio. Analysis of user movements is based on information captured by acceleration sensors integrated in mobile phone. The call alert functionality is then adjusted based on a combination of ambient audio level and physical activities of user.
Keywords: acceleration sensors, ambient audio, ambient context, call alert functionality, physical movements
ActivityMonitor: assisted life using mobile phones BIBAKFull-Text 417-418
  Hamed Ketabdar; Matti Lyra
In this work, we present a system and methodology for using mobile phones for monitoring physical activities of a user, and its applications in assisting elderly and people with need for special care and monitoring. The method is based on processing acceleration data provided by accelerometers integrated in mobile phones. This information is sent to a monitoring server, analyzed and presented as different health related factors for assistance, monitoring and healthcare purposes. A monitoring agent can use a desktop application to observe pattern of physical activities of several users in a live manner, and receive warnings in case of unexpected physical conditions. The data can be also stored offline for longer term analysis of physical behaviour and health. The desktop application also provides different options for managing, browsing, and searching activity related data.
Keywords: acceleration sensor, assisted life, desktop application, health related factors, live activity monitoring, mobile phones
The $3 recognizer: simple 3D gesture recognition on mobile devices BIBAKFull-Text 419-420
  Sven Kratz; Michael Rohs
We present the $3 Gesture Recognizer, a simple but robust gesture recognition system for input devices featuring 3D acceleration sensors. The algorithm is designed to be implemented quickly in prototyping environments, is intended to be device-independent and does not require any special toolkits or frameworks, but relies solely on simple trigonometric and geometric calculations. Our method requires significantly less training data than other gesture recognizers and is thus suited to be deployed and to deliver results rapidly.
Keywords: 3D gestures, classifier, gesture recognition, rapid prototyping, recognition rates, user interfaces
The RelFinder user interface: interactive exploration of relationships between objects of interest BIBAKFull-Text 421-422
  Steffen Lohmann; Philipp Heim; Timo Stegemann; Jürgen Ziegler
Being aware of the relationships that exist between objects of interest is crucial in many situations. The RelFinder user interface helps to get an overview: Even large amounts of relationships can be visualized, filtered, and analyzed by the user. Common concepts of knowledge representation are exploited in order to support interactive exploration both on the level of global filters and single relationships. The RelFinder is easy-to-use and works on every RDF knowledge base that provides standardized SPARQL access.
Keywords: dbpedia, decision support, graph visualization, linked data, relationship discovery, relationship web, semantic user interfaces, semantic web, sparql, visual exploration
Interactive machine translation using a web-based architecture BIBAKFull-Text 423-424
  Daniel Ortiz-Martínez; Luis A. Leiva; Vicent Alabau; Francisco Casacuberta
In this paper we present a new way of translating documents by using a Web-based system. An interactive approach is proposed as an alternative to post-editing the output of a machine translation system. In this approach, the user's feedback is used to validate or to correct parts of the system output that allow the generation of improved versions of the rest of the output.
Keywords: computer assisted translation, interactive machine translation, statistical machine translation
Haptic augmented reality dental trainer with automatic performance assessment BIBAKFull-Text 425-426
  Phattanapon Rhienmora; Kugamoorthy Gajananan; Peter Haddawy; Siriwan Suebnukarn; Matthew N. Dailey; Ekarin Supataratarn; Poonam Shrestha
We developed an augmented reality (AR) dental training simulator utilizing a haptic (force feedback) device. A number of dental procedures such as crown preparation and opening access to the pulp can be simulated with various shapes of dental drill. The system allows students to practise surgery in the correct postures as in the actual environment by combining 3D tooth and tool models upon the real-world view and displaying the result through a video see-through head mounted display (HMD). The system monitors the important features such as applied forces and tool movement that characterize the quality of the procedure. Automatic performance assessment is achieved by comparing outcome and process features of a student with the best matching expert. Moreover, we incorporated kinematic feedback and hand guidance by haptic device. The result from an initial evaluation shows that the simulator is promising for supplemental training.
Keywords: augmented reality, automatic performance assessment, dental surgical training, haptic device
QuickWoZ: a multi-purpose wizard-of-oz framework for experiments with embodied conversational agents BIBAKFull-Text 427-428
  Jan Smeddinck; Kamila Wajda; Adeel Naveed; Leen Touma; Yuting Chen; Muhammad Abu Hasan; Muhammad Waqas Latif; Robert Porzel
Herein we describe the QuickWoZ system, a Wizard-of-Oz (WoZ) tool that allows for the remote control of the behavior of animated characters in a 3D environment. The complete scene, character, behaviors and sounds can be defined in simple XML documents, which are parsed at runtime, so that setting up an experiment can be done without programming expertise. Quick selection lists and buttons enable the wizard to easily control the agents' behavior and allow for fast reactions to the subjects' input.
   The system is tailored for experiments with embodied conversational agents (ECAs) featuring multimodal interaction and was designed as a rapid prototyping system for evaluating the impact of an agent's behavior on the user.
Keywords: HCI, conversational agents, embodiment, evaluation
Agents as intelligent user interfaces for the net generation BIBAKFull-Text 429-430
  Han Yu; Yundong Cai; Zhiqi Shen; Xuehong Tao; Chunyan Miao
Riding on the back of the rapid expansion of the Internet, online virtual worlds which combine the prowess of interactive digital media and social networks have attained a high level of acceptance among the Net Generation users. This development prompted researchers to look into the potential of embedding learning contents into virtual worlds to create virtual learning environments (VLEs) that suit the need of the Net Generation learners. However, the special characteristics of virtual worlds that make them popular also pose great challenges to educators who wish to leverage their power. These challenges call for more sophisticated human computer interaction (HCI) mechanisms to assist learners to navigate the intriguing landscape of VLEs. In this paper, we demonstrate a teachable remembrance agent which acts as an intelligent user interface to provide innovative ways for students to interact with VLEs.
Keywords: interface agent, remembrance agent, teachable agent, virtual learning environment, virtual world


Workshop: eye gaze in intelligent human machine interaction BIBAKFull-Text 431-432
  Elisabeth André; Joyce Y. Chai
This workshop brought researchers from academia and industry together to share recent advances and discuss research directions and opportunities for next generation of intelligent human machine interaction that incorporate eye gaze.
Keywords: eye gaze, intelligent human machine interaction
Workshop on social recommender systems BIBAKFull-Text 433-434
  Ido Guy; Li Chen; Michelle X. Zhou
This workshop brought researchers from academia and industry together to share recent advances and discuss research directions for recommender systems in social media and Web 2.0. With social media sites becoming ubiquitous, the challenges and opportunities for recommendation technologies become greater, setting the grounds for new research and innovation.
Keywords: recommender systems, social media, social web, web 2.0
Visual interfaces to the social and semantic web (VISSW 2010) BIBAKFull-Text 435-436
  Siegfried Handschuh; Tom Heath; VinhTuan Thai; Ian Dickinson; Lora Aroyo; Valentina Presutti
Recent innovations in the Social and Semantic Web fields have resulted in large amounts of data created, published and consumed by users of the Web. This vast amount of data exists in a variety of formats, from the traditional ones such as text, image, video to the more recent additions such as streams of status information from Twitter and Facebook. The ability to easily integrate such vast amounts of data raises significant and exciting research challenges, not least of which how to provide effective access to and navigation across heterogeneous data sources on different platforms (e.g. computers, mobile devices, set-top boxes). Building on the success of the VISSW2009 workshop, the IUI2010 workshop on Visual Interfaces to the Social and Semantic Web aims to bring together researchers and practitioners from different fields to discuss the latest research results and challenges in designing, implementing, and evaluating intelligent interfaces supporting access, navigation and publishing of different types of contents on the Social and Semantic Web. This paper outlines the context of the workshop and provides an overview of the research to be presented at the event.
Keywords: social and semantic web, visual interfaces
1st international workshop on semantic models for adaptive interactive systems (SEMAIS 2010) BIBAKFull-Text 437-438
  Tim Hussein; Stephan G. Lukosch; Juergen Ziegler; Alan Dix
The International Workshop on Semantic Models for Adaptive Interactive Systems (SEMAIS 2010) aims to identify emerging trends in interactive system design using semantic models.
Keywords: adaptive interactive systems, interface design, model-driven user interfaces, semantic models, usability
Workshop on intelligent visual interfaces for text analysis BIBAKFull-Text 439-440
  Shixia Liu; Michelle X. Zhou; Giuseppe Carenini; Huamin Qu
This workshop brought together researchers and practitioners from both text analytics and interactive visualization communities to explore, define, and develop intelligent visual interfaces that help enhance the consumption and quality of complex text analysis results. Using this workshop as a starting point, we aim to foster closer, interdisciplinary relationships among researchers from text analytics and interactive visualization communities, so they can combine their expertise together to better tackle the difficult problems that face the text analytics community today.
Keywords: interactie visualization, text analytics, visual analytics
2nd multimodal interfaces for automotive applications (MIAA 2010) BIBAKFull-Text 441-442
  Michael Feld; Christian A. Müller; Tim Schwartz
This paper summarizes the main objectives of the 2nd IUI workshop on multimodal interfaces for automotive applications (MIAA 2010).
Keywords: automotive applications, human-machine-interaction, multimodal interfaces