The Adaptive Web

Methods and Strategies of Web Personalization

  • Editors
  • Peter Brusilovsky
  • Alfred Kobsa
  • Wolfgang Nejdl

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4321)

Table of contents

  1. Front Matter
  2. I. Modeling Technologies

    1. Front Matter
      Pages 1-1
    2. Susan Gauch, Mirco Speretta, Aravind Chandramouli, Alessandro Micarelli
      Pages 54-89
    3. Bamshad Mobasher
      Pages 90-135
    4. Alfred Kobsa
      Pages 136-154
    5. Alessandro Micarelli, Filippo Sciarrone, Mauro Marinilli
      Pages 155-192
  3. II. Adaptation Technologies

    1. Front Matter
      Pages 193-193
    2. Alessandro Micarelli, Fabio Gasparetti, Filippo Sciarrone, Susan Gauch
      Pages 195-230
    3. Alessandro Micarelli, Fabio Gasparetti
      Pages 231-262
    4. Peter Brusilovsky
      Pages 263-290
    5. J. Ben Schafer, Dan Frankowski, Jon Herlocker, Shilad Sen
      Pages 291-324
    6. Michael J. Pazzani, Daniel Billsus
      Pages 325-341
    7. Barry Smyth
      Pages 342-376
    8. Robin Burke
      Pages 377-408
    9. Andrea Bunt, Giuseppe Carenini, Cristina Conati
      Pages 409-432
    10. Luca Chittaro, Roberto Ranon
      Pages 433-462
  4. III. Applications

    1. Front Matter
      Pages 463-463
    2. Alison Cawsey, Floriana Grasso, Cécile Paris
      Pages 465-484
    3. Anna Goy, Liliana Ardissono, Giovanna Petrone
      Pages 485-520
    4. Antonio Krüger, Jörg Baus, Dominik Heckmann, Michael Kruppa, Rainer Wasinger
      Pages 521-549
    5. Daniel Billsus, Michael J. Pazzani
      Pages 550-570
  5. IV. Challenges

    1. Front Matter
      Pages 571-571
    2. Anthony Jameson, Barry Smyth
      Pages 596-627
    3. Alfred Kobsa
      Pages 628-670
    4. Peter Brusilovsky, Nicola Henze
      Pages 671-696
    5. Peter Dolog, Wolfgang Nejdl
      Pages 697-719
    6. Cristina Gena, Stephan Weibelzahl
      Pages 720-762
  6. Back Matter

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.


DOM Navigation adaptive systems agent technology association rules cognitive science collaborative filtering complexity content analysis data mining decision making document modeling machine learning recommender system semantic web

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2007
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science Computer Science (R0)
  • Print ISBN 978-3-540-72078-2
  • Online ISBN 978-3-540-72079-9
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
Industry Sectors
IT & Software