Learning user's preferences by analyzing Web-browsing behaviors
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Reorganizing web sites based on user access patterns
Proceedings of the tenth international conference on Information and knowledge management
Cognitive and task influences on Web searching behavior
Journal of the American Society for Information Science and Technology
Implicit feedback for inferring user preference: a bibliography
ACM SIGIR Forum
Display time as implicit feedback: understanding task effects
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 11th international conference on Intelligent user interfaces
A field study characterizing Web-based information-seeking tasks
Journal of the American Society for Information Science and Technology
User profiles for personalized information access
The adaptive web
Analysis of internet users' interests based on windows GUI messages
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: applications and services
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Identifying web sessions with simulated annealing
Expert Systems with Applications: An International Journal
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User profiling at client side is an important key task for intelligent information delivery in Web environment. However, several preprocessing also should be carried out prior to constructing user profiles. Moreover, the client side preprocessing should be carried out mostly based on usage logs without knowledge about contents and structures of Websites. In this perspective, we conducted an experiment in users’ natural Web environments during a period of several days, and analyzed collected usage logs and user feedbacks. Based on the results, we designed three important preprocessing techniques and evaluated the performances. We found that the required data preprocessing tasks can be conducted efficiently at client side based solely on usage logs.