ADAPTIVE HYPERTEXT AND HYPERMEDIA

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1 ADAPTIVE HYPERTEXT AND HYPERMEDIA

2 ADAPTIVE HYPERTEXT AND HYPERMEDIA Edited by Peter Brusilovsky Carnegie Mellon University Alfred Kobsa GMDFIT German National Research Centre for Information Technology and Julita Vassileva University of Saskatchewan SPRINGER-SCIENCE+BUSINESS MEDIA, B.V.

3 A C.I.P. Catalogue record for this book is available from the Library of Congress. ISBN ISBN (ebook) DOI / Printed on acid-free paper All Rights Reserved 1998 Springer Science+Business Media Dordrecht Originally published by Kluwer Academic Publishers in 1998 No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system, without written permission from the copyright owner.

4 PREFACE Hypertext/hypermedia systems and user-model based adaptive systems in the areas of learning and information retrieval have for a long time been considered as two mutually exclusive approaches to information access. Adaptive systems cater information to the user and may guide the user in the information space to present the most relevant material, taking into account a model of the user's goals, interests and preferences. Hypermedia systems, on the other hand, are "user neutral"; they provide the user with the tools and the freedom to explore an information space by browsing through a complex network of information nodes. Adaptive hypertext and hypermedia systems attempt to bridge the gap between these two approaches. Adaptation of hypermedia systems to each individual user is increasingly needed. With the growing size, complexity and heterogeneity of current hypermedia systems, such as the World Wide Web, it becomes virtually impossible to impose guidelines on authors concerning the overall organization of hypermedia information. The networks therefore become so complex and unstructured that the existing navigational tools are no longer powerful enough to provide orientation on where to search for the needed information. It is also not possible to identify appropriate pre-defined paths or subnets for users with certain goals and knowledge backgrounds since the user community of hypermedia systems is usually quite inhomogeneous. This is particularly true for Web-based applications which are expected to be used by a much greater variety of users than any earlier standalone application. A Web-based hypertext application which is designed with a particular class of users in mind may not suit users of other classes. A possible remedy for the negative effects of the traditional "one-size-fitsall" approach in the development of hypermedia systems is to equip them with the ability to adapt to the needs of their individual users. A possible way for achieving adaptivity is by modeling the users and tailoring the system's interactions to their goals, tasks and interests. In this sense, the notion of adaptive hypertext/hypermedia comes natural to denote a hypertext or hypermedia system which reflects some features of the user and/or characteristics of his system usage in a user model, and utilizes this model in order to adapt various behavioral aspects of the system to the user. Adaptive hypertext and hypermedia (for brevity, we will henceforth use the acronym AH) are a very new kind of user-model-based adaptive systems. Though they are well grounded in research on Intelligent Tutoring Systems, Help Systems and Information Retrieval Systems, real adaptive hypertext systems appeared less than 5 years ago. However, quite a few have been developed during the past four years. AH systems become increasingly important with the growing commercial availability of hypermedia applications. More and more users who have access to such systems are unfamiliar with them and/or v

5 VI their domains, and face difficulties in navigation and query formulation. The need for AH systems has also been recently recognized by the industry, and this field promises to become one of great commercial interest in the near future. This book is the first comprehensive publication on adaptive hypertext and hypermedia. It is oriented towards researchers and practitioners in the fields of hypertext and hypermedia, information systems, and personalized systems. It is also an important resource for the numerous developers of Web-based applications. The design decisions, adaptation methods, and experience presented in this book are a unique source of ideas and techniques for developing more usable and more intelligent Web-based systems suitable for a great variety of users. The practitioners will find it important that many of the adaptation techniques presented in this book proved to be efficient and are ready to be used in various applications. From a research point of view it is important that the papers in this book provide a topical state-of-the-art picture of adaptive hypertext and hypermedia problems and solutions. This book has its origin in the recently published special issue of User Modeling and User Adapted Interaction: An International Journal [I}. Since its publication, this special issue has become a source of creative ideas for many researchers on hypermedia and adaptive systems. The five papers which constitute the special issue are highly cited in many recent publications. User Modeling and User Adapted Interaction is a journal known as the primary source of high-quality papers on adaptive systems. It is not surprising that three earlier important full-size papers on adaptive hypertext were also published in this journal. The goal of this book is to make all these excellent papers available to a broader audience under a single cover. Altogether, this book is a collection of the currently most influential papers on adaptive hypertext and hypermedia. Brusilovsky's article provides a comprehensive state-of-the-art review of adaptive hypertext and hypermedia. This highly cited survey is centered around methods and techniques used in existing AH systems. The other papers go deeply into the characteristics of a particular AH system, attempt to generalize the major concerns that define adaptivity, or describe in detail a particular application. The paper by Kaplan, Fenwick and Chen is one of the first and most often referenced papers on adaptive navigation support.. It describes an on-line information system, HYPERFLEX, which can suggest an adaptively sorted list of relevant links, taking into account users' search goals and preferences. The results of two experiments with HYPERFLEX presented in the paper show that this kind of adaptive navigation support leads to more efficient navigation. Boyle and Encarnacion discuss the problems of expertise-adapted presentation in hypermedia systems. They present MetaDoc, one of the earliest and

6 most influential adaptive hypermedia systems. MetaDoc uses the stretchtext technique to adapt the content of hypermedia manual pages to the experience level of the user. Experiments with MetaDoc described in the paper show that adaptive stretchtext can increase reading comprehension without increasing document reading time. The paper by Hohl, Bocker and Gunzenhauser is the first archive publication of Hypadapter, an early adaptive hypertext system that gives individualized support in exploratory learning and programming in the domain of Common Lisp. The system employs domain and user modeling techniques to provide two principled types of assistance: individualized presentations of topic nodes and individualized navigation help. Beaumont's paper provides an example of an intelligent tutoring systems (ITS) with an adaptive hypermedia component. The system Anatom-Tutor presented in the paper demonstrates how a traditional ITS student model can be used to support hypermedia adaptation on the content level. Hook et al. discuss principles for adaptive interface design using a hypertext help system as an example, which is able to infer users' tasks and plans, and to provide appropriate help. Mathe and Chen describe an adaptive hypermedia information retrieval system which maintains an individual model of users' tasks, preferences, history, queries etc., in order to provide a complex secondary indexing scheme called "Adaptive Relevance Network". This network provides long-term adaptation based both on system usage and on explicit user input. Without any a priori specialized structure or statistical knowledge, the system evolves its dynamic indexing structure over time and allows users to quickly access information relevant to specific tasks. Vassileva takes the opposite approach of Mathe and Chen. She describes a deployed application of an adaptive hypermedia system for hospital information (namely a large loosely-coupled office documentation systems with underlying databases). The system limits the browsing space based on the current task performed by the user (tasks are defined a-priori by task-analysis), thus achieving higher efficiency in task performance. It also adapts the size of the browsing space and the direct search options available to the user's level of experience by gradually allowing the use of alternative indexing schemes. The editors hope that this book will shed new light on adaptation and user modeling in AH systems and will become a landmark on the road towards more user-friendly hypertext and hypermedia systems. Peter Brusilovsky Alfred Kobsa Julita Vassileva vii

7 PREFACE TABLE OF CONTENTS PETER BRUSILOVSKY Methods and Techniques of Adaptive Hypermedia CRA IG KAPLAN, JUST INE FENWICK and JAMES CHEN Adaptive Hypertext Navigation based on User Goals and Context. 45 CRAIG BOYLE and ANTONIO O. ENCARNACION Mctadoc: An Adaptive Hypertext Reading System [AN H. BEAUMONT User Modelling in the Interactive Anatomy Tutoring System ANATOM-TUTOR v HUBERTUS HOHL. HEINZ -DIETER BOCKER and RU L GUNZENHAUSER Hypadapter: An Adaptive Hypertext System for Exploratory Learning and Programming KRISTINA HOOK, JUSS I KARLGREN, ANNIKA WAERN, NILS DAHLBACK. CARL GUSTAF JANSSON, KLAS KARLGREN and BENOiT LEMAIRE A Glass Box Approach to Adaptive Hypermedia NATHALIE MATHE and JAMES R. CHEN User-Centered Indexing for Adaptive 11 formal ion Access JULITA VASSILEVA A Task-Centred Approach for User Modeling in a Hypermedia Office Documentation System INDEX

From Adaptive Hypermedia to the Adaptive Web Systems. WWW: One Size Fits All?

From Adaptive Hypermedia to the Adaptive Web Systems Peter Brusilovsky School of Information Sciences University of Pittsburgh, USA peterb@mail.sis.pitt.edu http://www.sis.pitt.edu/~peterb WWW: One Size