Peter’s research while affiliated with University of Pittsburgh and other places

One distinctive feature of any adaptive system is the user model that represents essential information about each user. This chapter complements other chapters of this book in reviewing user models and user modeling approaches applied in adaptive Web systems. The presentation is structured along three dimensions: what is being modeled, how it is modeled, and how the models are maintained. After a broad overview of the nature of the information presented in these various user models, the chapter focuses on two groups of approaches to user model representation and maintenance: the overlay approach to user model representation and the uncertainty-based approach to user modeling.

Traditional adaptive hypermedia systems have focused on providing adaptation functionality on a closed corpus, while Web search interfaces have delivered non-personalized information to users. In this paper, we show how we integrate closed corpus adaptation and global context provision in a Personal Reader environment. The local context consists of individually optimized recommendations to learning materials within the given corpus; the global context provides individually optimized recommendations to resources found on the Web, e.g., FAQs, student exercises, simulations, etc. The adaptive local context of a learning resource is generated by applying methods from adaptive educational hypermedia in a semantic web setting. The adaptive global context is generated by constructing appropriate queries, enrich them based on available user pro le information, and, if necessary, relax them during the querying process according to available metadata.

The challenge of the semantic web is the provision of distributed information with well defined meaning, understandable for different parties. Particularly, applications should be able to provide individually optimized access to information by taking the individual needs and requirements of the users into account. In this paper we propose a framework for personalized e-Learning in the semantic web and show how the semantic web resource description formats can be utilized for automatic generation of hypertext structures from distributed metadata. Ontologies and metadata for three types of resources (domain, user, and observation) are investigated. We investigate a logic-based approach to educational hypermedia using TRIPLE, a rule and query language for the semantic web.

Adaptive Systems use explicit user models representing user knowledge, goals, interests, etc. that enable them to tailor interaction to different users. Adaptive hypermedia and AdaptiveWeb have used this paradigm to allow personalization in hypertext systems and the WWW, with diverse applications ranging from museum guides to web-based education. The goal of this chapter is to present the history of adaptive hypermedia, introduce a number of classic but popular techniques, and discuss emerging research directions in the context of the Adaptive and Semantic Web, that challenge the adaptive hypermedia researchers in the new Millennium.

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 tailor 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 possible remedy for the negative effects of the traditional `one-size-fits-all' 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 of 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 naturally 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. 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 have proved to be efficient and are ready to be used in various applications.