Query expansion using local and global document analysis
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Improving automatic query expansion
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A study of smoothing methods for language models applied to Ad Hoc information retrieval
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ACES: a contextual engine for search
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Context-sensitive information retrieval using implicit feedback
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Personalizing search via automated analysis of interests and activities
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Implicit user modeling for personalized search
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Re-ranking search results using query logs
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Semi-automatic model integration using matching transformations and weaving models
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A personalized search engine based on Web-snippet hierarchical clustering
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A simple solution for improving the effectiveness of traditional information retrieval systems
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Predicting when browsing context is relevant to search
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Document relevance assessment via term distribution analysis using fourier series expansion
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Word distribution analysis for relevance ranking and query expansion
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Interactive information seeking via selective application of contextual knowledge
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Social summarization in collaborative web search
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Investigating retrieval performance with manually-built topic models
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Information at your fingertips: contextual IR in enterprise email
Proceedings of the 16th international conference on Intelligent user interfaces
Ontology-driven personalized query refinement
Journal of Web Engineering
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In this poster,we incorporate user query history, as context information, to improve the retrieval performance in interactive retrieval. Experiments using the TREC data show that incorporating such context information indeed consistently improves the retrieval performance in both average precision and precision at 20 documents.