Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Pointing the way: active collaborative filtering
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Using predictive prefetching to improve World Wide Web latency
ACM SIGCOMM Computer Communication Review
Fab: content-based, collaborative recommendation
Communications of the ACM
E-business: roadmap for success
E-business: roadmap for success
An Internet-based newspaper filtering and personalization system (demonstration abstract)
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Finance with a personalized touch
Communications of the ACM
Communications of the ACM
Communications of the ACM
Communications of the ACM
Communications of the ACM
Communications of the ACM
A personalized television listings service
Communications of the ACM
Personalization on the Net using Web mining: introduction
Communications of the ACM
Web usage mining for Web site evaluation
Communications of the ACM
Automatic personalization based on Web usage mining
Communications of the ACM
Communications of the ACM
Strategic Internet Marketing
E-Commerce
E-Business and E-Commerce for Managers
E-Business and E-Commerce for Managers
Information Technology for Management: Making Connections for Strategic Advantage,3rd Edition
Information Technology for Management: Making Connections for Strategic Advantage,3rd Edition
PIPE: Web Personalization by Partial Evaluation
IEEE Internet Computing
International Journal of Intelligent Systems Technologies and Applications
Adaptive Web SitesA Knowledge Extraction from Web Data Approach
Proceedings of the 2008 conference on Adaptive Web Sites: A Knowledge Extraction from Web Data Approach
A recommender system framework combining neural networks & collaborative filtering
IMCAS'06 Proceedings of the 5th WSEAS international conference on Instrumentation, measurement, circuits and systems
Personalised Information Retrieval: survey and classification
User Modeling and User-Adapted Interaction
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This chapter introduces a comprehensive review in personalization techniques and presents key features of personalized e-services. A framework is also introduced for integrating different personalization techniques into a single unified approach along the various segments of the customer decision process and it argues over the enhancement of the traditional personalization chain with an evaluation phase from which the results can provide feedback into the personalization techniques. Finally, based on the underlined approaches and assumptions, an extended personalization architecture is proposed including the evaluation layer. The vision of the authors is to embed a learning capability (through a fuzzy logic system, a neural network etc.) into the personalization techniques so that they avoid making the same unsuccessful suggestions in terms of links and features not being valued by the user. By achieving this goal, personalization-enabled web sites will behave as adaptive and evolutionary information systems.