
Intelligent Techniques for Web Personalization
IJCAI 2003 Workshop, ITWP 2003, Acapulco, Mexico, August 11, 2003, Revised Selected Papers
Springer (Publisher)
Published on 4. November 2005
Book
Paperback/Softback
VIII, 328 pages
978-3-540-29846-5 (ISBN)
Description
Web personalizationcan be de?ned as any set of actions that can tailor the Web experience to a particular user or set of users. The experience can be something as casualas browsinga Web site oras (economically)signi?cantas tradingstock or purchasing a car. The actions can range from simply making the presentation more pleasing to anticipating the needs of a user and providing customized and relevant information. To achieve e?ective personalization, organizations must rely on all available data, including the usage and click-stream data (re?e- ing user behavior), the site content, the site structure, domain knowledge, user demographics and pro?les. In addition, e?cient and intelligent techniques are needed to mine these data for actionable knowledge, and to e?ectively use the discovered knowledge to enhance the users' Web experience. These techniques must address important challenges emanating from the size and the heteroge- ity of the data, and the dynamic nature of user interactions with the Web. E-commerce and Web information systems are rich sources of di?cult pr- lems and challenges for AI researchers.
These challenges include the scalability of the personalization solutions, data integration, and successful integration of techniques from machine learning, information retrievaland ?ltering, databases, agent architectures, knowledge representation, data mining, text mining, stat- tics, user modelling and human-computer interaction. Throughout the history of the Web, AI has continued to play an essential role in the development of Web-based information systems, and now it is believed that personalization will prove to be the "killer-app" for AI.
These challenges include the scalability of the personalization solutions, data integration, and successful integration of techniques from machine learning, information retrievaland ?ltering, databases, agent architectures, knowledge representation, data mining, text mining, stat- tics, user modelling and human-computer interaction. Throughout the history of the Web, AI has continued to play an essential role in the development of Web-based information systems, and now it is believed that personalization will prove to be the "killer-app" for AI.
More details
Series
Edition
2005 ed.
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
VIII, 328 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 19 mm
Weight
517 gr
ISBN-13
978-3-540-29846-5 (9783540298465)
DOI
10.1007/11577935
Schweitzer Classification
Content
Intelligent Techniques for Web Personalization.- Intelligent Techniques for Web Personalization.- User Modelling.- Modeling Web Navigation: Methods and Challenges.- The Traits of the Personable.- Addressing Users' Privacy Concerns for Improving Personalization Quality: Towards an Integration of User Studies and Algorithm Evaluation.- Recommender Systems.- Case-Based Recommender Systems: A Unifying View.- Improving the Performance of Recommender Systems That Use Critiquing.- Hybrid Systems for Personalized Recommendations.- Enabling Technologies.- Collaborative Filtering Using Associative Neural Memory.- Scaling Down Candidate Sets Based on the Temporal Feature of Items for Improved Hybrid Recommendations.- Discovering Interesting Navigations on a Web Site Using SAM I .- Personalized Information Access.- Personalisation of Web Search.- The Compass Filter: Search Engine Result Personalization Using Web Communities.- Predicting Web Information Content.- Systems and Applications.- Mobile Portal Personalization: Tools and Techniques.- IKUM: An Integrated Web Personalization Platform Based on Content Structures and User Behavior.- A Semantic-Based User Privacy Protection Framework for Web Services.- Web Personalisation for Users Protection: A Multi-agent Method.