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UMUAI Tables of Contents: 0102030405060708091011121314151617181920

User Modeling and User-Adapted Interaction 10

Editors:Alfred Kobsa
Standard No:ISSN 0924-1868 (print) EISSN 1573-1391 (online)
Links:link.springer.com | Table of Contents
  1. UMUAI 2000-02 Volume 10 Issue 1
  2. UMUAI 2000 Volume 10 Issue 2/3
  3. UMUAI 2000 Volume 10 Issue 4

UMUAI 2000-02 Volume 10 Issue 1

ADAPT: A Predictive Cognitive Model of User Visual Attention and Action Planning BIBAKFull-Text 1-45
  Stephanie M. Doane; Young Woo Sohn
We present a computational cognitive model of novice and expert aviation pilot action planning called ADAPT that models performance in a dynamically changing simulated flight environment. We perform rigorous tests of ADAPT's predictive validity by comparing the performance of individual human pilots to that of their respective models. Individual pilots were asked to execute a series of flight maneuvers using a flight simulator, and their eye fixations and control movements were recorded in a time-synched database. Computational models of each of the 25 individual pilots were constructed, and the individual models simulated execution of the same flight maneuvers performed by the human pilots. The time-synched eye fixations and control movements of individual pilots and their respective models were compared, and rigorous tests of ADAPT's predictive validity were performed. The model explains and predicts a significant portion of pilot visual attention and control movements during flight as a function of piloting expertise. Implications for adaptive training systems are discussed.
Keywords: cognitive models; action planning; modeling expertise; hybrid models
The Evaluation of a Personalised Health Information System for Patients with Cancer BIBAKFull-Text 47-72
  Alison J. Cawsey; Ray B. Jones; Janne Pearson
In this paper we describe the evaluation of a personalised information system for patients with cancer. Our system dynamically generates hypertext pages that explain treatments, diseases, measurements etc related to the patient's condition, using information in the patient's medical record as the basis for the tailoring. We describe results of a controlled trial comparing this system with a nonpersonalised one. The results of the trial slow significant results concerning the patients' preferences for personalised information. We discuss the implications of our evaluation and results for the development and evaluation of future personalised systems, and adaptive hypertext systems in particular.
Keywords: empirical evaluation; tailored explanations; healthcare; dynamic hypertext; information systems; language generation

Book Review

Mark Maybury (Author), Intelligent Multimedia Information Retrieval BIBFull-Text 73-75
  Fiorella de Rosis

UMUAI 2000 Volume 10 Issue 2/3

Preface BIBFull-Text 77-80
  Sandra Carberry
Modeling Student Knowledge: Cognitive Tutors in High School and College BIBAKFull-Text 81-108
  Albert Corbett; Megan McLaughlin
This paper examines the role of adaptive student modeling in cognitive tutor research and dissemination. Cognitive tutorsTM are problem solving environments constructed around cognitive models of the knowledge students are acquiring. Over the past decade we in the Pittsburgh Advanced Cognitive Tutor (PACT) Center at Carnegie Mellon have been employing a cognitive programming tutor in university-based teaching and research, while simultaneously developing cognitive mathematics tutors that are currently in use in about 150 schools in 14 states. This paper examines adaptive student modeling issues in these two contexts. We examine the role of student modeling in making the transition from the research lab to widespread classroom use, describe our university-based efforts to empirically validate student modeling in the ACT Programming Tutor, and conclude with a description of the key role that student modeling plays in formative evaluations of the Cognitive Algebra II Tutor.
Keywords: student modeling; adaptivity; intelligent tutoring systems; mastery learning; empirical validation
Minimalist User Modelling in a Complex Commercial Software System BIBAKFull-Text 109-146
  Linda Strachan; John Anderson; Murray Sneesby
While user modelling has produced many research-based systems, comparatively little progress has been made in the development of user modelling components for commercial software systems. The development of minimalist user modelling components which are simplified to provide "just enough" assistance to a user through a pragmatic adaptive user interface is seen by many as an important step toward this goal. This paper describes the development, implementation, and evaluation of a minimalist user modelling component for the Tax and Investment Management Strategizer (TIMS), a complex commercial software system for financial management. This user modelling component manages several levels of adaptations designed to assist novice users in dealing with the complexity of this software package. Important issues and considerations for the development of user modelling components for commercial software systems and the evaluation of such systems in commercial settings are also discussed.
Keywords: pragmatic user modeling; knowledge-based systems; empirical evaluation; commercial software systems; financial planning
User Modeling for Adaptive News Access BIBAKFull-Text 147-180
  Daniel Billsus; Michael J. Pazzani
We present a framework for adaptive news access, based on machine learning techniques specifically designed for this task. First, we focus on the system's general functionality and system architecture. We then describe the interface and design of two deployed news agents that are part of the described architecture. While the first agent provides personalized news through a web-based interface, the second system is geared towards wireless information devices such as PDAs (personal digital assistants) and cell phones. Based on implicit and explicit user feedback, our agents use a machine learning algorithm to induce individual user models. Motivated by general shortcomings of other user modeling systems for Information Retrieval applications, as well as the specific requirements of news classification, we propose the induction of hybrid user models that consist of separate models for short-term and long-term interests. Furthermore, we illustrate how the described algorithm can be used to address an important issue that has thus far received little attention in the Information Retrieval community: a user's information need changes as a direct result of interaction with information. We empirically evaluate the system's performance based on data collected from regular system users. The goal of the evaluation is not only to understand the performance contributions of the algorithm's individual components, but also to assess the overall utility of the proposed user modeling techniques from a user perspective. Our results provide empirical evidence for the utility of the hybrid user model, and suggest that effective personalization can be achieved without requiring any extra effort from the user.
Keywords: user modeling; machine learning; information retrieval; intelligent agents; recommender systems
Recommender Systems for Learning: Building User and Expert Models through Long-Term Observation of Application Use BIBAKFull-Text 181-208
  Frank Linton; Hans-Peter Schaefer
Information technology has recently become the medium in which much professional office work is performed. This change offers an unprecedented opportunity to observe and record exactly how that work is performed. We describe our observation and logging processes and present an overview of the results of our long-term observations of a number of users of one desktop application. We then present our method of providing individualized instruction to each user by employing a new kind of user model and a new kind of expert model. The user model is based on observing the individual's behavior in a natural environment, while the expert model is based on pooling the knowledge of numerous individuals. Individualized instructional topics are selected by comparing an individual's knowledge to the pooled knowledge of her peers.
Keywords: agent; cluster analysis; data mining; instructional technology; instrumentation; knowledge acquisition; learning; logging; long-term observation; organizational learning; OWL; recommender system; sequence analysis; student modeling
A Review and Analysis of Commercial User Modeling Servers for Personalization on the World Wide Web BIBAKFull-Text 209-249
  Josef Fink; Alfred Kobsa
The aim of this article is to present and discuss selected commercial user modeling systems against the background of deployment requirements in real-world environments. Following the recent trend towards personalization on the World Wide Web, these systems are mainly aimed at supporting e-commerce including customer relationship management. In order to guide and structure our review, we define a requirements catalogue that comprises the main dimensions of functionality, data acquisition, representation, extensibility and flexibility, integration of external user-related information, compliance with standards, concern for privacy, and system architecture. Apart from the novelty of such a comparison both inside and outside the classical user modeling literature, a presentation of the core features of these commercial systems may provide a source of information and inspiration for the design, implementation, and deployment of future user modeling systems in research and commercial environments.
Keywords: personalization; one-to-one marketing; customer relationship management; electronic commerce; deployment requirements; commercial user modeling; company profiles; product reviews; user modeling servers

UMUAI 2000 Volume 10 Issue 4

Tailoring the Interaction with Users in Web Stores BIBAKFull-Text 251-303
  Liliana Ardissono; Anna Goy
We describe the user modeling and personalization techniques adopted in SETA, a prototype toolkit for the construction of adaptive Web stores which customize the interaction with users. The Web stores created using SETA suggest the items best fitting the customers' needs and adapt the layout and the description of the store catalog to their preferences and expertise. SETA uses stereotypical information to handle the user models and applies personalization rules to dynamically generate the hypertextual pages presenting products. The system adapts the graphical aspect, length and terminology used in the descriptions to parameters like the user's receptivity, expertise and interests. Moreover, it maintains a model associated with each person the goods are selected for; in this way, multiple criteria can be applied for tailoring the selection of items to the preferences of their beneficiaries.
Keywords: adaptive hypermedia; customization of Web stores; electronic shopping; knowledge-based approaches to the personalization of the interaction; personalized information presentation; user modeling

Book Review

Herbert Clarck, Using Language BIBFull-Text 305-308
  Sandra Carberry; Leah Schroeder
Gillian Brown, Speakers, Listeners, and Communication: Explorations in Discourse Analysis BIBFull-Text 309-313
  Susan McRoy