Abstract：Based on the query logs and news data provided by Sogou Lab, this paper studies judging queries involving implicit temporal intent and recognizing the implicit temporal attribute of these queries,and it also constructs the retrieval model of implicit temporal intent of queries.The experiment results show that the precision of temporal attributes recognition is 85% and the retrieval model can improve the effectiveness of ranking results.
张晓娟, 陆伟, 周红霞. 用户查询中潜在时间意图分析及其检索建模[J]. 现代图书情报技术, 2011, (11): 38-43.
Zhang Xiaojuan, Lu Wei, Zhou Hongxia. Analyzing and Retrieval Modeling on Implicit Temporal Intents in User's Queries. New Technology of Library and Information Service, DOI：10.11925/infotech.1003-3513.2011.11.06.
[1] Metzler D, Jones R, Peng F, et al. Improving Search Relevance for Implicitly Temporal Queries . In: Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval.2009. [2] Kanhabua N,Norvag K. Determining Time of Queries for Re-ranking Search Results . In:Proceedings of the 14th European Conference on Research and Advanced Technology for Digital Libraries. 2010:261-272. [3] Saracevic T. Relevance: A Review of the Literature and a Framework for Thinking on the Notion in Information Science. Part II: Nature and Manifestations of Relevance[J].Journal of the American Society for Information Science and Technology,2007,53(13):1915-1933. [4] Diaz F, Jones R. Using Temporal Profiles of Queries for Precision Prediction .In:Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.2004. [5] Nune S, Ribeiro C, David G. Using Neighbors to Date Web Documents . In: Proceedings of the 9th Annual ACM International Workshop on Web Information and Data Management.2007:129-136. [6] Alonso O, Gertz M, Baeza-Yates R. Clustering and Exploring Search Results Using Timeline Constructions .In:Proceedings of the 18th ACM Conference on Information and Knowledge Management.2009. [7] Alonso O, Gertz M. Clustering of Search Results Using Temporal Attributes . In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.2006. [8] Li X, Croft W B. Time-based Language Models . In:Proceedings of the 12th International Conference on Information and Knowledge Management.2003. [9] Berberich K, Bedathur S, Neumann J, et al. A Time Machine for Text Search . In:Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.2007. [10] Norvag K. Supporting Temporal Text-Containment Queries in Temporal Document Databases[J]. Journal of Data & Knowledge Engineering,2004,49 (1):105-125. [11] Sato N, Uehara M, Sakai Y. Temporal Ranking for Fresh Information Retrieval . In: Proceedings of the 6th International Workshop on Information Retrieval with Asian Languages.2003. [12] Jones R, Diaz F. Temporal Profiles of Queries[J]. ACM Transactions on Information Systems,2007,25(3):1-32. [13] Alonso O, Baeza-Yates R, Gertz G. Effectiveness of Temporal Snippets . In: Proceedings of the 18th International Conference on World Wide Web.2009. [14] Campos R, Jorge A M, Dias G. Using Web Snippets and Query-logs to Measure Implicit Temporal Intents in Queries . In: Proceedsings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval.2011. [15] 沈益舒.搜索语句的时间属性研究及其在检索排序中的应用 .杭州:浙江大学,2011. [16] Sougou查询日志 .http://www.sogou.com/labs/dl/q.html. [17] Liu Y, Zhang M, Ru L,et al. Automatic Query Type Identification Based on Click Through Information[J]. Information Retrieval Technology,2006:593-600. [18] Park K, Jee H, Lee T, et al. Automatic Extraction of User's Search Intention from Web Search Logs . Multimedia Tools and Applications.2011. http://posgrado.escom.ipn.mx/biblioteca/Automatic%20extraction%20of%20user%E2%80%99s%20search%20intention.pdf. [19] Sogou新闻数据 .http://www.sogou.com/labs/dl/cs.html.
