摘要: We tackle problems related to Web query formulation: given the set of keywords from a search session, 1) we find maximum promising query, and, 2) construct family queries covering all keywords. A is if it fulfills user-defined constraints on number returned hits. assume real-world setting where user not direct access engine's index, i.e., querying possible only through an interface. The goal be optimized overall submitted queries. For both develop strategies based co-occurrence probabilities. achieved performance gain substantial: compared uninformed baselines without probabilities expected savings are up 50% in queries, index accesses, and runtime.
acm.org
ieeecomputersociety.org参考文章(22)
James Allan, Giridhar Kumaran, A Case For Shorter Queries, and Helping Users Create Them north american chapter of the association for computational linguistics. pp. 220- 227 ,(2007)
Mitsuru Ishizuka, Danushka Bollegala, Yutaka Matsuo, An Integrated Approach to Measuring Semantic Similarity between Words Using Information Available on the Web north american chapter of the association for computational linguistics. pp. 340- 347 ,(2007)
Ben He, Iadh Ounis, Inferring Query Performance Using Pre-retrieval Predictors string processing and information retrieval. pp. 43- 54 ,(2004) , 10.1007/978-3-540-30213-1_5
Matthew Lease, James Allan, W. Bruce Croft, Regression Rank: Learning to Meet the Opportunity of Descriptive Queries Lecture Notes in Computer Science. pp. 90- 101 ,(2009) , 10.1007/978-3-642-00958-7_11
Giridhar Kumaran, James Allan, Effective and efficient user interaction for long queries Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '08. pp. 11- 18 ,(2008) , 10.1145/1390334.1390339
Giridhar Kumaran, Vitor R. Carvalho, Reducing long queries using query quality predictors international acm sigir conference on research and development in information retrieval. pp. 564- 571 ,(2009) , 10.1145/1571941.1572038
Giridhar Kumaran, James Allan, Adapting information retrieval systems to user queries Information Processing & Management. ,vol. 44, pp. 1838- 1862 ,(2008) , 10.1016/J.IPM.2007.12.006
Ziv Bar-Yossef, Maxim Gurevich, Random sampling from a search engine's index Journal of the ACM. ,vol. 55, pp. 1- 74 ,(2008) , 10.1145/1411509.1411514
Gang Luo, Chunqiang Tang, Hao Yang, Xing Wei, MedSearch Proceeding of the 17th ACM conference on Information and knowledge mining - CIKM '08. pp. 143- 152 ,(2008) , 10.1145/1458082.1458104
Jacob Shapiro, Isak Taksa, Constructing Web search queries from the user's information need expressed in a natural language Proceedings of the 2003 ACM symposium on Applied computing - SAC '03. pp. 1157- 1162 ,(2003) , 10.1145/952532.952758