The Adaptive Web

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

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