hotauthor: chen_y* : Human-Computer Interaction Bibliography Search

[1] Towards Providing On-Demand Expert Support for Software Developers Software and Programming Tools / Chen, Yan / Oney, Steve / Lasecki, Walter S. Proceedings of the ACM CHI'16 Conference on Human Factors in Computing Systems 2016-05-07 v.1 p.3192-3203

ACM Digital Library Link

Summary: Software development is an expert task that requires complex reasoning and the ability to recall language or API-specific details. In practice, developers often seek support from IDE tools, Web resources, or other developers to help fill in gaps in their knowledge on-demand. In this paper, we present two studies that seek to inform the design of future systems that use remote experts to support developers on demand. The first explores what types of questions developers would ask a hypothetical assistant capable of answering any question they pose. The second study explores the interactions between developers and remote experts in supporting roles. Our results suggest eight key system features needed for on-demand remote developer assistants to be effective, which has implications for future human-powered development tools.

[2] Motion Guidance Sleeve: Guiding the Forearm Rotation through External Artificial Muscles Did you feel the vibration -- Haptic Feedback Everywhere) / Chen, Chia-Yu / Chen, Yen-Yu / Chung, Yi-Ju / Yu, Neng-Hao Proceedings of the ACM CHI'16 Conference on Human Factors in Computing Systems 2016-05-07 v.1 p.3272-3276

ACM Digital Library Link

Summary: Online fitness videos make it possible and popular to do exercise at home. However, it is not easy to notice the details of motions by merely watching training videos. We propose a new type of motion guidance system that simulates the way that the human body moves as driven by muscle contractions. We have designed external artificial muscles on a sleeve to create a pulling sensation that can guide the forearm's pronation (internal rotation) and the forearm's supination (external rotation). The sleeve consists of stepper motors to provide pulling force, fishing lines and elastic bands to imitate muscle contraction to drive the forearm to rotate instinctively. We present two preliminary experiments. The first one shows that this system can effectively guide the forearm to rotate in the correct direction. The second one shows that users can be guided to the targeted angle by utilizing a tactile cue. We also report users' feedback through the experiments and provide design recommendations and directions for future research.

[3] Dot-it: Managing Nausea and Vomiting for A Peaceful Pregnancy with Personal Pattern Exploration Student Design Competition / Lee, Tzu-I / Chiang, Yih-Harn / Guo, Jiayi / Chen, Mu-Tsz / Chen, Yue Extended Abstracts of the ACM CHI'16 Conference on Human Factors in Computing Systems 2016-05-07 v.2 p.20-25

ACM Digital Library Link

Summary: Nausea and vomiting are the most common discomforts associated with pregnancy. Both significantly impact a pregnant woman's quality of life. Through research, we have discovered that nausea and vomiting have consistent daily patterns that pregnant women can leverage in order to manage their symptoms. However, without specific tools, a considerable amount of time would be spent trying to discover the pattern. Our work aims to help pregnant women find their pattern more quickly and avoid triggers. We present Dot-it, a system that allows pregnant women to record and pattern their NVP episodes so they can plan their daily schedules around their discomfort. Dot-it also facilitates emotional support by notifying pregnant women's partners their symptoms.

[4] Pactolus: A Method for Mid-Air Gesture Segmentation within EMG Late-Breaking Works: Extending User Capabilities / Chen, Yineng / Su, Xiaojun / Tian, Feng / Huang, Jin / Zhang, Xiaolong (Luke) / Dai, Guozhong / Wang, Hongan Extended Abstracts of the ACM CHI'16 Conference on Human Factors in Computing Systems 2016-05-07 v.2 p.1760-1765

ACM Digital Library Link

Summary: Mid-air gestures have become an important interaction technique in natural user interfaces, especially in augmented reality and virtual reality. Supporting a set of continuous gesture-based commands in mid-air gesture interaction systems, such as selecting and moving then placing an object, however, remains to be a challenge. This is largely because these intentional command gestures are connected through transitional, meaningless gestures, which are often misleading for gesture recognition systems. The inability to separate unintentional movements from intentional command gestures, also called the Midas problem, limits the application of mid-air gestures. This paper addresses the Midas problem via a physiological computing approach. With the help of sensors that capture physiological signals, we present a novel method, Pactolus, for segmenting mid-air gestures using arm electromyography. User studies demonstrate the high accuracy of our approach in segmenting mid-air gestures interleaved by transitional hand or finger movements.

[5] An Intelligent Assistant for High-Level Task Understanding Personalization / Sun, Ming / Chen, Yun-Nung / Rudnicky, Alexander I. Proceedings of the 2016 International Conference on Intelligent User Interfaces 2016-03-07 v.1 p.169-174

ACM Digital Library Link

Summary: People are able to interact with domain-specific intelligent assistants (IAs) and get help with tasks. But sometimes user goals are complex and may require interactions with multiple applications. However current IAs are limited to specific applications and users have to directly manage execution spanning multiple applications in order to engage in more complex activities. An ideal personal agent would be able to learn, over time, about tasks that span different resources. This paper addresses the problem of cross-domain task assistance in the context of spoken dialogue systems. We propose approaches to discover users' high-level intentions and using this information to assist users in their task. We collected real-life smartphone usage data from 14 participants and investigated how to extract high-level intents from users' descriptions of their activities. Our experiments show that understanding high-level tasks allows the agent to actively suggest apps relevant to pursuing particular user goals and reduce the cost of users' self-management.

[6] Dealing with Concept Drift in Exploratory Search: An Interactive Bayesian Approach Posters / Kangasrääsiö, Antti / Chen, Yi / Glowacka, Dorota / Kaski, Samuel Companion Proceedings of the 2016 International Conference on Intelligent User Interfaces 2016-03-07 v.2 p.62-66

ACM Digital Library Link

Summary: In exploratory search, when the user formulates a query iteratively through relevance feedback, it is likely that the feedback given earlier requires adjustment later on. The main reason for this is that the user learns while searching, which causes changes in the relevance of items and features as estimated by the user -- a phenomenon known as {it concept drift}. It might be helpful for the user to see the recent history of her feedback and get suggestions from the system about the accuracy of that feedback. In this paper we present a timeline interface that visualizes the feedback history, and a Bayesian regression model that can estimate jointly the user's current interests and the accuracy of each user feedback. We demonstrate that the user model can improve retrieval performance over a baseline model that does not estimate accuracy of user feedback. Furthermore, we show that the new interface provides usability improvements, which leads to the users interacting more with it.

[7] Social Incentives in Pervasive Fitness Apps for Obese and Diabetic patients Posters / Chen, Yu / Randriambelonoro, Mirana / Geissbuhler, Antoine / Pu, Pearl Companion Proceedings of ACM CSCW 2016 Conference on Computer-Supported Cooperative Work and Social Computing 2016-02-27 v.2 p.245-248

ACM Digital Library Link

Summary: Social incentives such as cooperation and competition are found to motivate users in pervasive fitness applications. This work investigates how social incentives work for individuals with obesity and diabetes. We used a mobile fitness application called HealthyTogether as an experimental platform, which allows dyads to achieve fitness goals together and compete in an online community. We conducted a four-week study with 16 obese and diabetic patients who used HealthyTogether to exercise with a buddy. Results show that participants exercised more with social incentives compared with their baseline. Collaborating with buddies to compete in a community was reported as motivating for dyads exercising with strong ties. Social interactions could be demotivating between dyads who did not know each other well. Finally, it is crucial to consider patients' technical literacy when designing behavior-changing technologies.

[8] LBSNShield: Malicious Account Detection in Location-Based Social Networks Posters / Xuan, Yuan / Chen, Yang / Li, Huiying / Hui, Pan / Shi, Lei Companion Proceedings of ACM CSCW 2016 Conference on Computer-Supported Cooperative Work and Social Computing 2016-02-27 v.2 p.437-440

ACM Digital Library Link

Summary: Given the popularity of GPS-enabled smart devices, location-based social networks (LBSNs) have attracted numerous users around the world. The openness of LBSN platforms has also made themselves the targets of malicious attackers. In LBSNs, attackers can register a number of fake identities and let them post spam reviews or fake checkins. Therefore, discovering and blocking the malicious accounts are vital for the experience of legitimate users. In this paper, we investigated how to accurately detect malicious accounts in LBSNs. We collected rich user data from a popular LBSN in China, so-called Dianping. We then built a crowdsourcing based annotation platform to mark legitimate and malicious accounts. By examining the annotated data set, we selected a number of key features to distinguish between these two types of accounts. Based on these features, we built LBSNShield, a machine learning-based malicious account detection system. According to our extensive evaluation, our system can achieve an F1-score of 0.89.

[9] Comparing bare-hand-in-air Gesture and Object-in-hand Tangible User Interaction for Navigation of 3D Objects in Modeling Work-in-Progress / Dangeti, Sanmathi / Chen, Yingjie Victor / Zheng, Chunhui Proceedings of the 2016 International Conference on Tangible and Embedded Interaction 2016-02-14 p.417-421

ACM Digital Library Link

Summary: 3D modeling is used in Computer Graphics in various fields. Since the growth of gestures, virtual reality and embodied cognition, there have been various new technologies developed to either improve the modeling efficiency, or to provide more nature intuitive experience to the users. In this paper, from the user experience perspective, we try to compare these methods for navigation of 3D objects in the virtual modeling environment including: simple bare hand gestures, tangible user interfaces (TUI) with object in hand, as well as mouse/keyboard as the primary input. Based on embodied cognition theory, we hypothesis that the object-in-hand method might bring better user experience since the interaction between the object and hand can enhance the user's cognition while navigating a model. We present a conceptual design, with two approaches and three design models which demonstrate differences in user interaction with 3D modeling software.

[10] Efficient intrinsic image decomposition for RGBD images Rendering & ray tracing / Shi, Jian / Dong, Yue / Tong, Xin / Chen, Yanyun Proceedings of the 2015 ACM Symposium on Virtual Reality Software and Technology 2015-11-13 p.17-25

ACM Digital Library Link

Summary: Intrinsic image decomposition is a longstanding problem in computer vision. In this paper, we present a novel approach for efficiently decomposing an RGBD image into its reflectance and shading components. A robust super-pixel segmentation method is employed to select piece-wise constant reflectance regions and reduce the total number of unknowns. With the use of depth information, low frequency environment light can be represented by spherical harmonics and solved with super-pixels. After that, pixels that do not belong to any super-pixel are solved based on the super-pixels' shading. Compared to existing works, which often depend on the color Retinex assumption, our algorithm does not require any chromaticity-based constraints and enables us to solve many challenging cases such as color lighting environments and gray-scale textures. We also design an efficient solver for our system, and with our GPU implementation, it achieves 10-23 fps and boosts the decomposition process to real-time performance, enabling a wide range of applications such as dynamic object recoloring, re-texturing and virtual object composition.

[11] Vector solid texture synthesis using two-scale shaping model Rendering & ray tracing / Qian, Yinling / Shu, Yue / Sun, Hanqiu / Chen, Yanyun Proceedings of the 2015 ACM Symposium on Virtual Reality Software and Technology 2015-11-13 p.27-36

ACM Digital Library Link

Summary: Solid textures exhibit several benefits over traditional texture mapping, such as no demanding for parameterization and providing internal information. However, the difficulty in accessing and high memory consumption seriously limit the usage of solid textures. We present an efficient approach to directly synthesize vector solid textures comprising 3D particles from 2D examples. Two-scale shaping model is introduced to automatically and accurately reconstruct 3D particle outlines from 2D cross sections. Low frequency spherical harmonics are used to morph smooth outlines while high frequency ones model particle surface details. These outlines are further converted to signed distance field grids for vector representation. Particle volume color is represented by radial basis functions. We arrange particles using simplified particle proxies to improve efficiency. Particles' position offsets are calculated according to the particle itself and one-ring neighbor particles' shapes iteratively. Finally, our cell-building algorithm constructs containers and computes scale for each particle instance. Experiments show that our algorithm can generate vector solid textures with plausible 3D particles.

[12] Leveraging Behavioral Patterns of Mobile Applications for Personalized Spoken Language Understanding Oral Session 3: Language, Speech and Dialog / Chen, Yun-Nung / Sun, Ming / Rudnicky, Alexander I. / Gershman, Anatole Proceedings of the 2015 International Conference on Multimodal Interaction 2015-11-09 p.83-86

ACM Digital Library Link

Summary: Spoken language interfaces are appearing in various smart devices (e.g. smart-phones, smart-TV, in-car navigating systems) and serve as intelligent assistants (IAs). However, most of them do not consider individual users' behavioral profiles and contexts when modeling user intents. Such behavioral patterns are user-specific and provide useful cues to improve spoken language understanding (SLU). This paper focuses on leveraging the app behavior history to improve spoken dialog systems performance. We developed a matrix factorization approach that models speech and app usage patterns to predict user intents (e.g. launching a specific app). We collected multi-turn interactions in a WoZ scenario; users were asked to reproduce the multi-app tasks that they had performed earlier on their smart-phones. By modeling latent semantics behind lexical and behavioral patterns, the proposed multi-model system achieves about 52% of turn accuracy for intent prediction on ASR transcripts.

[13] Capturing AU-Aware Facial Features and Their Latent Relations for Emotion Recognition in the Wild Grand Challenge 2: Emotion Recognition in the Wild Challenge 2015 / Yao, Anbang / Shao, Junchao / Ma, Ningning / Chen, Yurong Proceedings of the 2015 International Conference on Multimodal Interaction 2015-11-09 p.451-458

ACM Digital Library Link

Summary: The Emotion Recognition in the Wild (EmotiW) Challenge has been held for three years. Previous winner teams primarily focus on designing specific deep neural networks or fusing diverse hand-crafted and deep convolutional features. They all neglect to explore the significance of the latent relations among changing features resulted from facial muscle motions. In this paper, we study this recognition challenge from the perspective of analyzing the relations among expression-specific facial features in an explicit manner. Our method has three key components. First, we propose a pair-wise learning strategy to automatically seek a set of facial image patches which are important for discriminating two particular emotion categories. We found these learnt local patches are in part consistent with the locations of expression-specific Action Units (AUs), thus the features extracted from such kind of facial patches are named AU-aware facial features. Second, in each pair-wise task, we use an undirected graph structure, which takes learnt facial patches as individual vertices, to encode feature relations between any two learnt facial patches. Finally, a robust emotion representation is constructed by concatenating all task-specific graph-structured facial feature relations sequentially. Extensive experiments on the EmotiW 2015 Challenge testify the efficacy of the proposed approach. Without using additional data, our final submissions achieved competitive results on both sub-challenges including the image based static facial expression recognition (we got 55.38% recognition accuracy outperforming the baseline 39.13% with a margin of 16.25%) and the audio-video based emotion recognition (we got 53.80% recognition accuracy outperforming the baseline 39.33% and the 2014 winner team's final result 50.37% with the margins of 14.47% and 3.43%, respectively).

[14] CyclopsRing: Enabling Whole-Hand and Context-Aware Interactions Through a Fisheye Ring Session 8A: Hands and Fingers / Chan, Liwei / Chen, Yi-Ling / Hsieh, Chi-Hao / Liang, Rong-Hao / Chen, Bing-Yu Proceedings of the 2015 ACM Symposium on User Interface Software and Technology 2015-11-05 v.1 p.549-556

ACM Digital Library Link

Summary: This paper presents CyclopsRing, a ring-style fisheye imaging wearable device that can be worn on hand webbings to enable whole-hand and context-aware interactions. Observing from a central position of the hand through a fisheye perspective, CyclopsRing sees not only the operating hand, but also the environmental contexts that involve with the hand-based interactions. Since CyclopsRing is a finger-worn device, it also allows users to fully preserve skin feedback of the hands. This paper demonstrates a proof-of-concept device, reports the performance in hand-gesture recognition using random decision forest (RDF) method, and, upon the gesture recognizer, presents a set of interaction techniques including on-finger pinch-and-slide input, in-air pinch-and-motion input, palm-writing input, and their interactions with the environmental contexts. The experiment obtained an 84.75% recognition rate of hand gesture input from a database of seven hand gestures collected from 15 participants. To our knowledge, CyclopsRing is the first ring-wearable device that supports whole-hand and context-aware interactions.

[15] Efficient Activity Retrieval through Semantic Graph Queries Session 7: Actions and Events / Castanon, Gregory / Chen, Yuting / Zhang, Ziming / Saligrama, Venkatesh Proceedings of the 2015 ACM International Conference on Multimedia 2015-10-26 p.391-400

ACM Digital Library Link

Summary: We present an efficient retrieval approach for activity detection in large surveillance video datasets based on semantic graph queries. Unlike conventional approaches, our zero-shot retrieval method does not require knowledge of the activity classes contained in the video. We propose a novel user-centric approach that models queries through the creation of sparse semantic graphs based on attributes and discriminative relationships. We then pose search as a ranked subgraph matching problem and leverage the fact that the attributes and relationships in the query have different levels of discriminability to filter out bad matches. Rather than solving the NP-hard exact subgraph matching problem, we develop a novel maximally discriminative spanning tree (MDST) as the relaxation of a given query graph, and then describe a matching algorithm that recovers matches to this tree in linear time using maximally discriminative subgraphmatching (MDSM).
We utilize the MDST to minimize the number of possible matches to the original query while guaranteeing that the best matches are within this set. We test this algorithm on two large video datasets: the 35-GB Virat Ground dataset and a 1-TB aerial data collection from Yuma. These datasets yield graphs with 200,000 nodes and 1 million nodes, respectively, with an average degree of 5. Our approach finds complex, large-scale queries in seconds while maintaining comparable precision and recall to slower current approaches.

[16] Pan360: INS Assisted 360-Degree Panorama (Demo Description) Demos 2: / Lin, Yu-Hsin / Chen, Yu-Mei / Chu, Lun-Cheng / Chen, Andre / Liao, Scott Chien-Hung / Chang, Edward Y. Proceedings of the 2015 ACM International Conference on Multimedia 2015-10-26 p.795-796

ACM Digital Library Link

Summary: This article describes Pan360, a 360 X 180 panorama capturing and viewing product developed and launched by our team, and our demo plan.

[17] Filter-Invariant Image Classification on Social Media Photos Poster Session 1 / Chen, Yu-Hsiu / Chao, Ting-Hsuan / Bai, Sheng-Yi / Lin, Yen-Liang / Chen, Wen-Chin / Hsu, Winston H. Proceedings of the 2015 ACM International Conference on Multimedia 2015-10-26 p.855-858

ACM Digital Library Link

Summary: With the popularity of social media nowadays, tons of photos are uploaded everyday. To understand the image content, image classification becomes a very essential technique for plenty of applications (e.g., object detection, image caption generation). Convolutional Neural Network (CNN) has been shown as the state-of-the-art approach for image classification. However, one of the characteristics in social media photos is that they are often applied with photo filters, especially on Instagram. We find that prior works do not aware of this trend in social media photos and fail on filtered images. Thus, we propose a novel CNN architecture that utilizes the power of pairwise constraint by combining Siamese network and the proposed adaptive margin contrastive loss with our discriminative pair sampling method to solve the problem of filter bias. To the best of our knowledge, this is the first work to tackle filter bias on CNN and achieve state-of-the-art performance on a filtered subset of ILSVRC2012.

[18] Viewability Prediction for Online Display Ads Session 2E: Users and Predictions / Wang, Chong / Kalra, Achir / Borcea, Cristian / Chen, Yi Proceedings of the 2015 ACM Conference on Information and Knowledge Management 2015-10-19 p.413-422

ACM Digital Library Link

Summary: As a massive industry, display advertising delivers advertisers' marketing messages to attract customers through graphic banners on webpages. Advertisers are charged by ad serving, where their ads are shown in web pages. However, recent studies show that about half of the ads were actually never seen by users because they do not scroll deep enough to bring the ads in-view. Thus, the ad pricing standards are shifting to a new model: ads are paid if they are in view, not just being served. To the best of our knowledge, this paper is the first to address the important problem of ad viewability prediction which can improve the performance of guaranteed ad delivery, real-time bidding, as well as recommender systems. We analyze a real-life dataset from a large publisher, identify a number of features that impact the scroll depth for a given user and a page, and propose a probabilistic latent class model that predicts the viewability of any given scroll depth for a user-page pair. The experiments demonstrate that our model outperforms comparison systems based on singular value decomposition and logistic regression, in terms of prediction quality and training time.

[19] Does Vertical Bring more Satisfaction?: Predicting Search Satisfaction in a Heterogeneous Environment Session 8B: Web Search / Chen, Ye / Liu, Yiqun / Zhou, Ke / Wang, Meng / Zhang, Min / Ma, Shaoping Proceedings of the 2015 ACM Conference on Information and Knowledge Management 2015-10-19 p.1581-1590

ACM Digital Library Link

Summary: The study of search satisfaction is one of the prime concerns in search performance evaluation research. Most existing works on search satisfaction primarily rely on the hypothesis that all results on search engine result pages (SERPs) are homogeneous. However, a variety of heterogeneous vertical results such as videos, images and instant answers are aggregated into SERPs by search engines to improve the diversity and quality of search results. In this paper, we carry out a lab-based user study with specifically designed SERPs to determine how verticals with different qualities and presentation styles affect search satisfaction. Users' satisfaction feedback and external assessors' satisfaction annotations are both collected to make a comparison regarding the perception of search satisfaction. Mouse click-through / movement data and eye movement information are also collected such that we can investigate the influence of vertical results from the perspectives of both benefit and cost. Finally, a vertical-aware learning-based prediction method is proposed to predict search satisfaction on aggregated SERPs. To the best of our knowledge, this paper is the first to analyze the effect of verticals on search satisfaction. The results show that verticals with different qualities, presentation styles and positions have different effects on search satisfaction, among which Encyclopedia verticals, as well as Download verticals, will bring the largest improvement. Furthermore, our proposed vertical-aware prediction method outperforms state-of-the-art methods that are designed for search satisfaction prediction in homogeneous environment.

[20] A Real-Time Eye Tracking Based Query Expansion Approach via Latent Topic Modeling Short Papers: Information Retrieval / Chen, Yongqiang / Zhang, Peng / Song, Dawei / Wang, Benyou Proceedings of the 2015 ACM Conference on Information and Knowledge Management 2015-10-19 p.1719-1722

ACM Digital Library Link

Summary: Formulating and reformulating reliable textual queries have been recognized as a challenging task in Information Retrieval (IR), even for experienced users. Most existing query expansion methods, especially those based on implicit relevance feedback, utilize the user's historical interaction data, such as clicks, scrolling and viewing time on documents, to derive a refined query model. It is further expected that the user's search experience would be largely improved if we could dig out user's latent query intention, in real-time, by capturing the user's current interaction at the term level directly. In this paper, we propose a real-time eye tracking based query expansion method, which is able to: (1) automatically capture the terms that the user is viewing by utilizing eye tracking techniques; (2) derive the user's latent intent based on the eye tracking terms and by using the Latent Dirichlet Allocation (LDA) approach. A systematic user study has been carried out and the experimental results demonstrate the effectiveness of our proposed methods.

[21] Different Users, Different Opinions: Predicting Search Satisfaction with Mouse Movement Information Session 6B: Predicting / Liu, Yiqun / Chen, Ye / Tang, Jinhui / Sun, Jiashen / Zhang, Min / Ma, Shaoping / Zhu, Xuan Proceedings of the 2015 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2015-08-09 p.493-502

ACM Digital Library Link

Summary: Satisfaction prediction is one of the prime concerns in search performance evaluation. It is a non-trivial task for two major reasons: (1) The definition of satisfaction is rather subjective and different users may have different opinions in satisfaction judgement. (2) Most existing studies on satisfaction prediction mainly rely on users' click-through or query reformulation behaviors but there are many sessions without such kind of interactions. To shed light on these research questions, we construct an experimental search engine that could collect users' satisfaction feedback as well as mouse click-through/movement data. Different from existing studies, we compare for the first time search users' and external assessors' opinions on satisfaction. We find that search users pay more attention to the utility of results while external assessors emphasize on the efforts spent in search sessions. Inspired by recent studies in predicting result relevance based on mouse movement patterns (namely motifs), we propose to estimate the utilities of search results and the efforts in search sessions with motifs extracted from mouse movement data on search result pages (SERPs). Besides the existing frequency-based motif selection method, two novel selection strategies (distance-based and distribution-based) are also adopted to extract high quality motifs for satisfaction prediction. Experimental results on over 1,000 user sessions show that the proposed strategies outperform existing methods and also have promising generalization capability for different users and queries.

[22] Opinion Spammer Detection in Web Forum Short Papers / Chen, Yu-Ren / Chen, Hsin-Hsi Proceedings of the 2015 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2015-08-09 p.759-762

ACM Digital Library Link

Summary: In this paper, a real case study on opinion spammer detection in web forum is presented. We explore user profiles, maximum spamicity of first posts of users, burstiness of registration of user accounts, and frequent poster set to build a model with SVM with RBF kernel and frequent itemset mining. The proposed model achieves 0.6753 precision, 0.6190 recall, and 0.6460 F1 score. The result is promising because the ratio of opinion spammers in the test set is only 0.98%.

[23] BeaconPass: A Location Based APP Game for Traveler Universal Access to Mobile Interaction / Ho, Tsung-Yuan / Chen, Chien-Hsu / Chien, Sheng-Fen / Chen, Yi-Hsuan / Liu, Su-Yu / Bayona, Juan Sebastian UAHCI 2015: 9th International Conference on Universal Access in Human-Computer Interaction, Part I: Access to Today's Technologies 2015-08-02 v.1 p.288-297

Keywords: Ibeacon; Location based game; APP; Traveler; Service design; Mobile application

Link to Digital Content at Springer

Summary: BeaconPass is a smartphone/tablet application inspired by shared problems among travelers. Following our previews research; lack of internet access, GPS inaccuracy, battery life and insufficient site-specific information, reflect on travelers getting lost and missing on their touring expectations. Thus it was decided that the application's goal is to narrow the gap between previously planned activities and the exploration of a city. Beacon technology was selected as the means, from which the application would develop, to ease the exploration of a city. Given the potential that beacon technology holds for showcasing a wide offer of visiting alternatives, on a site-specific basis, the application has been packaged into a game that seeks to encourage the traveler to meet unplanned locations. Graphically, the game uses a "pirate's journey" metaphor that allows the user to level up while engaging in an open exploration of the city.

[24] Application of Infrared Technology in Household Water Tap Design and Evaluation Ergonomics and Universal Access / Chen, Ming-Shih / Li, Ming-Lun / Chen, Yu-Chia UAHCI 2015: 9th International Conference on Universal Access in Human-Computer Interaction, Part IV: Access to the Human Environment and Culture 2015-08-02 v.4 p.432-443

Keywords: Infrared technology; Universal design; Washing behavior; Water tap; Use evaluation

Link to Digital Content at Springer

Summary: Based on previous research results, this study examined the use of water taps and observes the experiences of different age groups when using new product designs. The results indicated that, although new designs can meet the demands of different generations, first-time users have a relatively low understanding of a product from its appearance; hence, if a new design deviates from common user cognition, even it could solve user problems, it still has low user acceptance.

[25] Understanding Gratifications of Watching Danmaku Videos -- Videos with Overlaid Comments Cross-Cultural Design Methods and Case Studies / Chen, Yue / Gao, Qin / Rau, Pei-Luen Patrick CCD 2015: 7th International Conference on Cross-Cultural Design Methods, Practice and Impact 2015-08-02 v.1 p.153-163

Keywords: Danmaku comment; Gratifications; Co-viewing; Video-sharing sites

Link to Digital Content at Springer

Summary: Danmaku comment is a comment technology that overlays user comments directly on the video and creates a co-viewing experience. It originates from Japan and becomes increasingly popular on video sharing sites in China, particularly among the young generation. This exploratory study investigates reasons for watching Danmaku videos through two focus group studies. The results show that the users who watch Danmaku videos found it a way to entertain themselves, to be in company, to have the sense of belonging, and to seek information. Those who do not watch Danmaku videos, however, complained about the abundance of information, the imperfect information quality, and the look and feel. We summarized scenarios suitable for Danmaku commenting from three perspectives: the content, the complexity of information, and the number of viewers. Possible improvements and new applications of Danmaku commenting were discussed.