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2007 | Book

User Models for Adaptive Hypermedia and Adaptive Educational Systems Read chapter Read first chapter

The Adaptive Web

Methods and Strategies of Web Personalization

Editors: Peter Brusilovsky, Alfred Kobsa, Wolfgang Nejdl

Publisher: Springer Berlin Heidelberg

Book Series : Lecture Notes in Computer Science

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

Following the increase in of the information available on the Web, the diversity of its users and the complexity of Web applications, researchers started developing adaptive Web systems that tailored their appearance and behavior to each individual user or user group. Adaptive systems were designed for different usage contexts, exploring different kinds of personalization. Web personalization has evolved into a large research field attracting scientists from different communities such as hypertext, user modeling, machine learning, natural language generation, information retrieval, intelligent tutoring systems, cognitive science, and Web-based education.

This state-of-the-art survey provides a systematic overview of the ideas and techniques of the adaptive Web and serves as a central source of information for researchers, practitioners, and students. The volume constitutes a comprehensive and carefully planned collection of chapters, mapping out the most important areas of the adaptive Web, each solicited from experts and leaders in the field.

The largest part of the book focuses on personalization techniques, namely the modeling side of personalization (Chaps. 1-5), and on adaptation, (Chaps. 6-14). The technique-focused part is complemented by four domain-oriented chapters in the third section of the book (Chaps. 15-18). The last section is devoted to recently emerging topics; it provides a prospective view of the new ideas and techniques that are moving rapidly into the focus of the adaptive Web community and gives the reader a glimpse into the not-so-distant future.

Table of Contents

Frontmatter

I. Modeling Technologies

Frontmatter
User Models for Adaptive Hypermedia and Adaptive Educational Systems
Abstract
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.
Peter Brusilovsky, Eva Millán
User Profiles for Personalized Information Access
Abstract
The amount of information available online is increasing exponentially. While this information is a valuable resource, its sheer volume limits its value. Many research projects and companies are exploring the use of personalized applications that manage this deluge by tailoring the information presented to individual users. These applications all need to gather, and exploit, some information about individuals in order to be effective. This area is broadly called user profiling. This chapter surveys some of the most popular techniques for collecting information about users, representing, and building user profiles. In particular, explicit information techniques are contrasted with implicitly collected user information using browser caches, proxy servers, browser agents, desktop agents, and search logs. We discuss in detail user profiles represented as weighted keywords, semantic networks, and weighted concepts. We review how each of these profiles is constructed and give examples of projects that employ each of these techniques. Finally, a brief discussion of the importance of privacy protection in profiling is presented.
Susan Gauch, Mirco Speretta, Aravind Chandramouli, Alessandro Micarelli
Data Mining for Web Personalization
Abstract
In this chapter we present an overview of Web personalization process viewed as an application of data mining requiring support for all the phases of a typical data mining cycle. These phases include data collection and pre-processing, pattern discovery and evaluation, and finally applying the discovered knowledge in real-time to mediate between the user and the Web. This view of the personalization process provides added flexibility in leveraging multiple data sources and in effectively using the discovered models in an automatic personalization system. The chapter provides a detailed discussion of a host of activities and techniques used at different stages of this cycle, including the preprocessing and integration of data from multiple sources, as well as pattern discovery techniques that are typically applied to this data. We consider a number of classes of data mining algorithms used particularly for Web personalization, including techniques based on clustering, association rule discovery, sequential pattern mining, Markov models, and probabilistic mixture and hidden (latent) variable models. Finally, we discuss hybrid data mining frameworks that leverage data from a variety of channels to provide more effective personalization solutions.
Bamshad Mobasher
Generic User Modeling Systems
Abstract
This chapter reviews research results in the field of Generic User Modeling Systems. It describes the purposes of such systems, their services within user-adaptive systems, and the different design requirements for research prototypes and commercial deployments. It discusses the architectures that have been explored so far, namely shell systems that form part of the application, central server systems that communicate with several applications, and possible future agent-based user modeling systems. Major implemented research proto types and commercial systems are briefly described.
Alfred Kobsa
Web Document Modeling
Abstract
A very common issue of adaptive Web-Based systems is the modeling of documents. Such documents represent domain-specific information for a number of purposes. Application areas such as Information Search, Focused Crawling and Content Adaptation (among many others) benefit from several techniques and approaches to model documents effectively. For example, a document usually needs preliminary processing in order to obtain the relevant information in an effective and useful format, so as to be automatically processed by the system. The objective of this chapter is to support other chapters, providing a basic overview of the most common and useful techniques and approaches related with document modeling. This chapter describes high-level techniques to model Web documents, such as the Vector Space Model and a number of AI approaches, such as Semantic Networks, Neural Networks and Bayesian Networks. This chapter is not meant to act as a substitute of more comprehensive discussions about the topics presented. Rather, it provides a brief and informal introduction to the main concepts of document modeling, also focusing on the systems that are presented in the rest of the book as concrete examples of the related concepts.
Alessandro Micarelli, Filippo Sciarrone, Mauro Marinilli

II. Adaptation Technologies

Frontmatter
Personalized Search on the World Wide Web
Abstract
With the exponential growth of the available information on the World Wide Web, a traditional search engine, even if based on sophisticated document indexing algorithms, has difficulty meeting efficiency and effectiveness performance demanded by users searching for relevant information. Users surfing the Web in search of resources to satisfy their information needs have less and less time and patience to formulate queries, wait for the results and sift through them. Consequently, it is vital in many applications - for example in an e-commerce Web site or in a scientific one - for the search system to find the right information very quickly. Personalized Web environments that build models of short-term and long-term user needs based on user actions, browsed documents or past queries are playing an increasingly crucial role: they form a winning combination, able to satisfy the user better than unpersonalized search engines based on traditional Information Retrieval (IR) techniques. Several important user personalization approaches and techniques developed for the Web search domain are illustrated in this chapter, along with examples of real systems currently being used on the Internet.
Alessandro Micarelli, Fabio Gasparetti, Filippo Sciarrone, Susan Gauch
Adaptive Focused Crawling
Abstract
The large amount of available information on the Web makes it hard for users to locate resources about particular topics of interest. Traditional search tools, e.g., search engines, do not always successfully cope with this problem, that is, helping users to seek the right information. In the personalized search domain, focused crawlers are receiving increasing attention, as a well-founded alternative to search the Web. Unlike a standard crawler, which traverses the Web downloading all the documents it comes across, a focused crawler is developed to retrieve documents related to a given topic of interest, reducing the network and computational resources. This chapter presents an overview of the focused crawling domain and, in particular, of the approaches that include a sort of adaptivity. That feature makes it possible to change the system behavior according to the particular environment and its relationships with the given input parameters during the search.
Alessandro Micarelli, Fabio Gasparetti
Adaptive Navigation Support
Abstract
Adaptive navigation support is a specific group of technologies that support user navigation in hyperspace, by adapting to the goals, preferences and knowledge of the individual user. These technologies, originally developed in the field of adaptive hypermedia, are becoming increasingly important in several adaptive Web applications, ranging from Web-based adaptive hypermedia to adaptive virtual reality. This chapter provides a brief introduction to adaptive navigation support, reviews major adaptive navigation support technologies and mechanisms, and illustrates these with a range of examples.
Peter Brusilovsky
Collaborative Filtering Recommender Systems
Abstract
One of the potent personalization technologies powering the adaptive web is collaborative filtering. Collaborative filtering (CF) is the process of filtering or evaluating items through the opinions of other people. CF technology brings together the opinions of large interconnected communities on the web, supporting filtering of substantial quantities of data. In this chapter we introduce the core concepts of collaborative filtering, its primary uses for users of the adaptive web, the theory and practice of CF algorithms, and design decisions regarding rating systems and acquisition of ratings. We also discuss how to evaluate CF systems, and the evolution of rich interaction interfaces. We close the chapter with discussions of the challenges of privacy particular to a CF recommendation service and important open research questions in the field.
J. Ben Schafer, Dan Frankowski, Jon Herlocker, Shilad Sen
Content-Based Recommendation Systems
Abstract
This chapter discusses content-based recommendation systems, i.e., systems that recommend an item to a user based upon a description of the item and a profile of the user’s interests. Content-based recommendation systems may be used in a variety of domains ranging from recommending web pages, news articles, restaurants, television programs, and items for sale. Although the details of various systems differ, content-based recommendation systems share in common a means for describing the items that may be recommended, a means for creating a profile of the user that describes the types of items the user likes, and a means of comparing items to the user profile to determine what to re commend. The profile is often created and updated automatically in response to feedback on the desirability of items that have been presented to the user.
Michael J. Pazzani, Daniel Billsus
Case-Based Recommendation
Abstract
Recommender systems try to help users access complex information spaces. A good example is when they are used to help users to access online product catalogs, where recommender systems have proven to be especially useful for making product suggestions in response to evolving user needs and preferences. Case-based recommendation is a form of content-based recommendation that is well suited to many product recommendation domains where individual products are described in terms of a well defined set of features (e.g., price, colour, make, etc.). These representations allow case-based recommenders to make judgments about product similarities in order to improve the quality of their recommendations and as a result this type of approach has proven to be very successful in many e-commerce settings, especially when the needs and preferences of users are ill-defined, as they often are. In this chapter we will describe the basic approach to case-based recommendation, highlighting how it differs from other recommendation technologies, and introducing some recent advances that have led to more powerful and flexible recommender systems.
Barry Smyth
Hybrid Web Recommender Systems
Abstract
Adaptive web sites may offer automated recommendations generated through any number of well-studied techniques including collaborative, content-based and knowledge-based recommendation. Each of these techniques has its own strengths and weaknesses. In search of better performance, researchers have combined recommendation techniques to build hybrid recommender systems. This chapter surveys the space of two-part hybrid recommender systems, comparing four different recommendation techniques and seven different hybridization strategies. Implementations of 41 hybrids including some novel combinations are examined and compared. The study finds that cascade and augmented hybrids work well, especially when combining two components of differing strengths.
Robin Burke
Adaptive Content Presentation for the Web
Abstract
In this chapter we describe techniques for adaptive presentation of content on the Web. We first describe techniques to select and structure the content deemed to be most relevant for the current user in the current interaction context. We then illustrate approaches that deal with the problem of how to adaptively deliver this content.
Andrea Bunt, Giuseppe Carenini, Cristina Conati
Adaptive 3D Web Sites
Abstract
In recent years, technological developments have made it possible to build interactive 3D models of objects and 3D Virtual Environments that can be experienced through the Web, using common, low-cost personal computers. As in the case of Web-based hypermedia, adaptivity can play an important role in increasing the usefulness, effectiveness and usability of 3D Web sites, i.e., Web sites distributing 3D content. This paper introduces the reader to the concepts, issues and techniques of adaptive 3D Web sites.
Luca Chittaro, Roberto Ranon

III. Applications

Frontmatter
Adaptive Information for Consumers of Healthcare
Abstract
This chapter discusses the application of some of the technologies of the adaptive web to the problem of providing information for healthcare consumers. The particular issues relating to this application area are discussed, including the goals of the communication, typical content of a user model, and commonly used techniques. Two case studies are presented, and evaluation approaches considered.
Alison Cawsey, Floriana Grasso, Cécile Paris
Personalization in E-Commerce Applications
Abstract
This chapter is about personalization and adaptation in electronic commerce (e-commerce) applications. In the first part, we briefly introduce the challenges posed by e-commerce and we discuss how personalization strategies can help companies to face such challenges. Then, we describe the aspects of personalization, taken as a general technique for the customization of services to the user, which have been successfully employed in e-commerce Web sites. To conclude, we present some emerging trends and and we discuss future perspectives.
Anna Goy, Liliana Ardissono, Giovanna Petrone
Adaptive Mobile Guides
Abstract
In this chapter we discuss various aspects of adaptive mobile guide applications. After having motivated the need for web based mobile applications, we will discuss technologies that are needed to enable adaptive mobile web applications, including not only positioning technologies but also sensor technologies needed to determine additional information on the context and situation of usage. We will also address issues of modeling context and situations before giving an overview on existing systems coming from three important classes of mobile guides: museum guides, navigation systems and shopping assistants. The chapter closes with an extensive discussion of relevant attributes of web based mobile guides.
Antonio Krüger, Jörg Baus, Dominik Heckmann, Michael Kruppa, Rainer Wasinger
Adaptive News Access
Abstract
This chapter describes how the adaptive web technologies discussed in this book have been applied to news access. First, we provide an overview of different types of adaptivity in the context of news access and identify corresponding algorithms. For each adaptivity type, we briefly discuss representative systems that use the described techniques. Next, we discuss an in-depth case study of a personalized news system. As part of this study, we outline a user modeling approach specifically designed for news personalization, and present results from an evaluation that attempts to quantify the effect of adaptive news access from a user perspective. We conclude by discussing recent trends and novel systems in the adaptive news space.
Daniel Billsus, Michael J. Pazzani

IV. Challenges

Frontmatter
Adaptive Support for Distributed Collaboration
Abstract
Through interaction with others, a person develops multiple perspectives that become the basis for innovation and the construction of new knowledge. This chapter discusses the challenges facing emerging web-based technologies that enable distributed users to discover and construct new knowledge collaboratively. Examples include advanced collaborative and social information filtering technology that not only helps users discover knowledge, peers, and relevant communities, but also plays a powerful role in facilitating and mediating their interaction. As the internet extends around the world and interconnects diverse cultures, the adaptive web will be challenged to provide a personalized knowledge interface that carries new perspectives to diverse communities. It will play the role of an interface for knowledge construction, a mediator for communication and understanding, and a structured channel through which knowledge is created, interpreted, used, and recreated by other users.
Amy Soller
Recommendation to Groups
Abstract
Recommender systems have traditionally recommended items to individual users, but there has recently been a proliferation of recommenders that address their recommendations to groups of users. The shift of focus from an individual to a group makes more of a difference than one might at first expect. This chapter discusses the most important new issues that arise, organizing them in terms of four subtasks that can or must be dealt with by a group recommender: 1. acquiring information about the user’s preferences; 2. generating recommendations; 3. explaining recommendations; and 4. helping users to settle on a final decision. For each issue, we discuss how it has been dealt with in existing group recommender systems and what open questions call for further research.
Anthony Jameson, Barry Smyth
Privacy-Enhanced Web Personalization
Abstract
Consumer studies demonstrate that online users value personalized content. At the same time, providing personalization on websites seems quite profitable for web vendors. This win-win situation is however marred by privacy concerns since personalizing people’s interaction entails gathering considerable amounts of data about them. As numerous recent surveys have consistently demonstrated, computer users are very concerned about their privacy on the Internet. More over, the collection of personal data is also subject to legal regulations in many countries and states. Both user concerns and privacy regulations impact frequently used personalization methods. This article analyzes the tension between personal ization and privacy, and presents approaches to reconcile the both.
Alfred Kobsa
Open Corpus Adaptive Educational Hypermedia
Abstract
Despite the fact that adaptive hypermedia techniques have proven their ability to provide user guidance and orientation in hyperspace, we do not currently see the widespread adoption of these techniques. A couple of reasons may explain this phenomenon. One of them is the current lack of re-usability and interoperability between adaptive techniques/systems, which – to some degree – originates in the so-called “open corpus problem” found in adaptive hypermedia. In this article, we analyze this problem in a popular arena: adaptive hypermedia systems with an emphasis on education. The origins and effects of the open corpus problem are discussed, and recent approaches are demonstrated that have – in one way or the other – developed as strategies for solving the open corpus problem. We summarize these findings and discuss how solution strategies can be successfully employed in the future, enabling adaptive hypermedia techniques within open, dynamic information spaces, such as the Semantic Web.
Peter Brusilovsky, Nicola Henze
Semantic Web Technologies for the Adaptive Web
Abstract
Ontologies and reasoning are the key terms brought into focus by the semantic web community. Formal representation of ontologies in a common data model on the web can be taken as a foundation for adaptive web technologies as well. This chapter describes how ontologies shared on the semantic web provide conceptualization for the links which are a main vehicle to access information on the web. The subject domain ontologies serve as constraints for generating only those links which are relevant for the domain a user is currently interested in. Furthermore, user model ontologies provide additional means for deciding which links to show, annotate, hide, generate, and reorder. The semantic web technologies provide means to formalize the domain ontologies and metadata created from them. The formalization enables reasoning for personalization decisions. This chapter describes which components are crucial to be formalized by the semantic web ontologies for adaptive web. We use examples from an eLearning domain to illustrate the principles which are broadly applicable to any information domain on the web.
Peter Dolog, Wolfgang Nejdl
Usability Engineering for the Adaptive Web
Abstract
This chapter discusses a usability engineering approach for the design and the evaluation of adaptive web-based systems, focusing on practical issues. A list of methods will be presented, considering a user-centered approach. After having introduced the peculiarities that characterize the evaluation of adaptive web-based systems, the chapter describes the evaluation methodologies following the temporal phases of evaluation, according to a user-centered approach. Three phases are distinguished: requirement phase, preliminary evaluation phase, and final evaluation phase. Moreover, every technique is classified according to a set of parameters that highlight the practical exploitation of that technique. For every phase, the appropriate techniques are described by giving practical examples of their application in the adaptive web. A number of issues that arise when evaluating an adaptive system are described, and potential solutions and workarounds are sketched.
Cristina Gena, Stephan Weibelzahl
Backmatter
Metadata
Title
The Adaptive Web
Editors
Peter Brusilovsky
Alfred Kobsa
Wolfgang Nejdl
Copyright Year
2007
Publisher
Springer Berlin Heidelberg
Electronic ISBN
978-3-540-72079-9
Print ISBN
978-3-540-72078-2
DOI
https://doi.org/10.1007/978-3-540-72079-9

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