%0 Conference Paper %1 citeulike:1281701 %A Tan, Bin %A Shen, Xuehua %A Zhai, ChengXiang %B Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining %C New York, NY, USA %D 2006 %I ACM %K social-search %P 718--723 %R 10.1145/1150402.1150493 %T Mining Long-term Search History to Improve Search Accuracy %U http://dx.doi.org/10.1145/1150402.1150493 %X Long-term search history contains rich information about a user's search preferences, which can be used as search context to improve retrieval performance. In this paper, we study statistical language modeling based methods to mine contextual information from long-term search history and exploit it for a more accurate estimate of the query language model. Experiments on real web search data show that the algorithms are effective in improving search accuracy for both fresh and recurring queries. The best performance is achieved when using clickthrough data of past searches that are related to the current query. %@ 1-59593-339-5

@inproceedings{citeulike:1281701, abstract = {{Long-term search history contains rich information about a user's search preferences, which can be used as search context to improve retrieval performance. In this paper, we study statistical language modeling based methods to mine contextual information from long-term search history and exploit it for a more accurate estimate of the query language model. Experiments on real web search data show that the algorithms are effective in improving search accuracy for both fresh and recurring queries. The best performance is achieved when using clickthrough data of past searches that are related to the current query.}}, added-at = {2018-03-19T12:24:51.000+0100}, address = {New York, NY, USA}, author = {Tan, Bin and Shen, Xuehua and Zhai, ChengXiang}, biburl = {https://www.bibsonomy.org/bibtex/2ea2a5de06e38cf8077c346f8676555b3/aho}, booktitle = {Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining}, citeulike-article-id = {1281701}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1150402.1150493}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1150402.1150493}, doi = {10.1145/1150402.1150493}, interhash = {31e94e7ee589365db6956336cbd00fe0}, intrahash = {ea2a5de06e38cf8077c346f8676555b3}, isbn = {1-59593-339-5}, keywords = {social-search}, location = {Philadelphia, PA, USA}, pages = {718--723}, posted-at = {2016-01-18 16:40:07}, priority = {2}, publisher = {ACM}, series = {KDD '06}, timestamp = {2018-03-19T12:24:51.000+0100}, title = {{Mining Long-term Search History to Improve Search Accuracy}}, url = {http://dx.doi.org/10.1145/1150402.1150493}, year = 2006 }