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Adaptive and Personalized Semantic Web

  • Spiros Sirmakessis

Part of the Studies in Computational Intelligence book series (SCI, volume 14)

Table of contents

  1. Front Matter
    Pages I-XI
  2. Christos Makris, Yannis Panagis, Evangelos Sakkopoulos, Athanasios Tsakalidis
    Pages 1-10
  3. Maria Rigou, Spiros Sirmakessis, Giannis Tzimas
    Pages 37-55
  4. Thanyalak Maneewatthana, Gary Wills, Wendy Hall
    Pages 65-74
  5. C. Alexakos, B. Vassiliadis, K. Votis, S. Likothanassis
    Pages 75-83
  6. Christian Schindler, Pranjal Arya, Andreas Rath, Wolfgang Slany
    Pages 85-94
  7. Dimitrios A. Koutsomitropoulos, Markos F. Fragakis, Theodoros S. Papatheodorou
    Pages 95-105

About this book

Introduction

Web Personalization can be defined as any set of actions that can tailor the Web experience to a particular user or set of users. To achieve effective personalization, organizations must rely on all available data, including the usage and click-stream data (reflecting user behaviour), the site content, the site structure, domain knowledge, as well as user demographics and profiles. In addition, efficient and intelligent techniques are needed to mine this data for actionable knowledge, and to effectively use the discovered knowledge to enhance the users' Web experience. The aim of the International Workshop on Adaptive and Personalized Semantic Web that was held in the Sixteenth ACM Conference on Hypertext and Hypermedia (September 6-9, 2005, Salzburg, Austria) was to bring together researchers and practitioners in the fields of web engineering, adaptive hypermedia, semantic web technologies, knowledge management, information retrieval, user modelling, and other related disciplines which provide enabling technologies for personalization and adaptation on the World Wide Web. The book contains the papers presented during the workshop. Presentations of the papers are available online at www.hci.gr.

Keywords

Personalization Text Mining and Knowledge Management Theory and Applications Web Engineering Web Intelligence Web Mining algorithm algorithms knowledge discovery knowledge management model modeling ontology organization semantic web

Editors and affiliations

  • Spiros Sirmakessis
    • 1
  1. 1.Research AcademicComputer Technology InstitutePatrasGreece

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-33279-0
  • Copyright Information Springer 2006
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-30605-4
  • Online ISBN 978-3-540-33279-4
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site