Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
Implicit feedback for inferring user preference: a bibliography
ACM SIGIR Forum
An analysis of web searching by European AlltheWeb.com users
Information Processing and Management: an International Journal
Evaluating implicit measures to improve web search
ACM Transactions on Information Systems (TOIS)
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
Utilizing a geometry of context for enhanced implicit feedback
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
A basis for information retrieval in context
ACM Transactions on Information Systems (TOIS)
Discovering and using groups to improve personalized search
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Search Engines: Information Retrieval in Practice
Search Engines: Information Retrieval in Practice
How are we searching the World Wide Web? A comparison of nine search engine transaction logs
Information Processing and Management: an International Journal - Special issue: Formal methods for information retrieval
ACM Transactions on Computer-Human Interaction (TOCHI)
Improving tag recommendation using social networks
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
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The paper is concerned with the design and the evaluation of the combination of user interaction and informative content features for implicit and pseudo feedback-based document re-ranking. The features are observed during the visit of the top-ranked documents returned in response to a query. Experiments on a TREC Web test collection have been carried out and the experimental results are illustrated. We report that the effectiveness of the combination of user interaction for implicit feedback depends on whether document re-ranking is on a single-user or a user-group basis. Moreover, the adoption of document re-ranking on a user-group basis can improve pseudo-relevance feedback by providing more effective document for expanding queries.