Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic query expansion using query logs
Proceedings of the 11th international conference on World Wide Web
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Selecting good expansion terms for pseudo-relevance feedback
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Mining term association patterns from search logs for effective query reformulation
Proceedings of the 17th ACM conference on Information and knowledge management
Analysis of long queries in a large scale search log
Proceedings of the 2009 workshop on Web Search Click Data
Exploring reductions for long web queries
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Clickthrough-based translation models for web search: from word models to phrase models
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Predicting query performance using query, result, and user interaction features
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
Proceedings of the fifth ACM international conference on Web search and data mining
Session-based query performance prediction
Proceedings of the 21st ACM international conference on Information and knowledge management
Robust query rewriting using anchor data
Proceedings of the sixth ACM international conference on Web search and data mining
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Query expansion for Information Retrieval is a challenging task. On the one hand, low quality expansion may hurt either recall, due to vocabulary mismatch, or precision, due to topic drift, and therefore reduce user satisfaction. On the other hand, utilizing a large number of expansion terms for a query may easily lead to resource consumption overhead. As web search engines apply strict constraints on response time, it is essential to estimate the impact of each expansion term on query performance at the pre-retrieval time. Our experimental results confirm that a significant part of expansions do not improve query performance, and it is possible to detect such expansions at the pre-retrieval time.