ACM SIGIR Forum
Implicit feedback for inferring user preference: a bibliography
ACM SIGIR Forum
Understanding user goals in web search
Proceedings of the 13th international conference on World Wide Web
Display time as implicit feedback: understanding task effects
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Evaluating implicit measures to improve web search
ACM Transactions on Information Systems (TOIS)
Automatic identification of user goals in Web search
WWW '05 Proceedings of the 14th international conference on World Wide Web
Learning user interaction models for predicting web search result preferences
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
A study on the effects of personalization and task information on implicit feedback performance
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Identifying and improving retrieval for procedural questions
Information Processing and Management: an International Journal
Describing and predicting information-seeking behavior on the Web
Journal of the American Society for Information Science and Technology
Search behaviors in different task types
Proceedings of the 10th annual joint conference on Digital libraries
Personalizing information retrieval for multi-session tasks: the roles of task stage and task type
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Helping identify when users find useful documents: examination of query reformulation intervals
Proceedings of the third symposium on Information interaction in context
Predicting task difficulty for different task types
Proceedings of the 73rd ASIS&T Annual Meeting on Navigating Streams in an Information Ecosystem - Volume 47
Analysis and evaluation of query reformulations in different task types
Proceedings of the 73rd ASIS&T Annual Meeting on Navigating Streams in an Information Ecosystem - Volume 47
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One major problem of most current information retrieval systems is that they provide uniform access and retrieval results to all users solely based on the query terms users issued to the system. In this paper, we propose a model to personalize the search results according to the user's search context, in particular the type of task that led the user to engage in information-seeking behavior, and the behaviors that the user has engaged in during the search. The point of this personalization is to predict potentially useful documents based on the type of task, and on behaviors indicative of document usefulness. We believe this model can improve individual users' retrieval performance substantially.