CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Hourly analysis of a very large topically categorized web query log
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Time-dependent semantic similarity measure of queries using historical click-through data
Proceedings of the 15th international conference on World Wide Web
Search result re-ranking by feedback control adjustment for time-sensitive query
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Scaling high-order character language models to gigabytes
Software '05 Proceedings of the Workshop on Software
Leveraging temporal dynamics of document content in relevance ranking
Proceedings of the third ACM international conference on Web search and data mining
Towards recency ranking in web search
Proceedings of the third ACM international conference on Web search and data mining
Understanding temporal query dynamics
Proceedings of the fourth ACM international conference on Web search and data mining
The effects of time on query flow graph-based models for query suggestion
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
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To model time-dependent user intent for Web search, this paper proposes a novel method using machine learning techniques to exploit temporal features for effective time-sensitive search result re-ranking. We propose models to incorporate users' click through information for queries that are seen in the training data, and then further extend the model to deal with unseen queries considering the relationship between queries. Experiment shows significant improvement on search result ranking over original search outputs.