Evolution of the Web in the artificial intelligence environment
Nayak, Richi, Ichalkaranje, Nikhil, & Jain, Lakhmi (Eds.) (2008) Evolution of the Web in the artificial intelligence environment. Studies in Computational Intelligence, 130. Springer, Berlin Heidelberg.
The Web has revolutionized the way we seek information on all aspects of education, entertainment, business, health and so on. The Web has evolved into a publishing medium, global electronic market and increasingly, a platform for conducting electronic commerce. A part of this success can be attributed to the tremendous advances made in the Artificial Intelligence field. The popularity of the Web has opened many opportunities to develop smart Web-based systems using artificial intelligence techniques.
There exist numerous Web technology and applications that can benefit with the application of artificial intelligence techniques. It is not possible to cover them all in one book with a required degree of quality, depth and width. We present this book to discuss some important Web developments by using artificial intelligence techniques in the areas of Web personalisation, semantic Web and Web services.
Chapter 1 will introduce the different topics discussed in this book. Chapter 2 will discuss a broad overview of these Web developments that are evolved with artificial intelligence techniques to improve the Web functionality. Chapters 3, 4 and 5 discuss the problems and advancements in Personalisation in the areas of the Web personalisation with user profiles, the personalisation of Web contents in mobile devices and the personalisation of Web services respectively. Chapters 6 and 7 discuss the problems of intelligently composing and discovering appropriate Web services respectively. Chapters 8 and 9 will cover the issue of semantic operability problem in Semantic Web by discussing the various concepts of meta in computing and advancements in Emergent Semantics respectively. Chapter 10 presents a smart Web-based system by discussing an intelligent tutoring system based on Bayesian networks. Finally, chapter 11 draws the similarity and distinction between various Web-based collective decision-making systems such as recommender system, folksonmy, document ranking, etc.
The primary readers of this book are undergraduate/postgraduate students, researchers and practitioners in information technology and computer science related areas.
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|Keywords:||Web Intelligence, Data Mining, Web Personalisation|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2008 Springer|
|Deposited On:||03 Mar 2009 10:59|
|Last Modified:||03 Mar 2009 10:59|
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