期刊文献+

一种基于时间感知的搜索引擎模型 被引量:1

A temporal-aw are model for search engine
原文传递
导出
摘要 目前许多用户查询与网页信息的时效性密切相关,但当前的搜索引擎在处理许多具有时间属性的查询时还不尽如人意。通过引入基于时间感知的用户查询理解、索引结构和页面排序算法,提出一种基于用户查询日志挖掘的时间感知搜索引擎模型,来克服当前主流搜索引擎在处理具有时效性查询时存在的不足。在真实的Web环境下广泛进行的实验结果表明了该模型的有效性。 Many of web pages have freshness and nowadays many users' queries are closely related to this freshness For current search engines, however, there are still some problems in handling many queries with time property. A new temporal-aware search engine model was presented, which introduces the user query understanding, index structure and page ranking algorithm based on the temporal-aware processing into architecture of search engine. This model aims at o- vercome the shortcoming of the traditional keyword-based search engine in dealing with the time-based queries. Exten- sive experiments are carried out in a real Web environment, and the experimental results show the effectiveness of the model.
出处 《山东大学学报(理学版)》 CAS CSCD 北大核心 2013年第11期80-86,共7页 Journal of Shandong University(Natural Science)
基金 国家自然科学基金资助项目(61272109) 国家星火计划项目(2012GA750007) 河南省科技厅基础与前沿技术研究项目(122300410378) 河南省教育厅科学技术研究重点项目(13A520032 12A120002) 湖北省教育科学"十一五"规划课题项目(2010B178)
关键词 信息时效性 搜索引擎模型 查询日志挖掘 页面排序 freshness of information search engine model query log mining page ranking
  • 相关文献

参考文献15

  • 1YU Philip S, LI Xin, LIU Bing. Adding the temporal di- mension to search-a case study in publication search [ C ]//Proceedings of the International Conference on Web Intelligence ( W1 2005 ). Washington : IEEE Computer Society, 2005:543-549.
  • 2Pablo Castells, Miriam Fernandez, David Vallet. An ad- aptation of the vector-space model for ontology-based in- formation retrieval [J]. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2007, 19(2) :261-272.
  • 3CHENG Xiangzhai, JOHN D. Lafferty: a study of smoothing methods for language models applied to ad hoc information retrieval[C]//Proceedings of the 24st Inter- national ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2001 ). New York: ACM Press, 2001:334-342.
  • 4Yasuhiro Fujiwara, Makoto Nakatsuji, Hiroaki Shiokawa, et al. Fast and exact top-k algorithm for PageRank[C]// Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence ( AAAI 2013 ). [ S. l. ] : AAAI Press, 2013 : 1106-1112.
  • 5Jon M Kleinberg. Authoritative sources in a hyperlinked environment[J]. Journal of the ACM, 1999, 46 ( 5 ) : 604-632.
  • 6NIE Zaiqing, WEN Jirong, MA Weiying. Object-level vertical search[ C]//Proceedings of 3rd Biennial Confer- ence on Innovative Data Systems Research ( CIDR 2007 ). [ S. l, ] : [ s. n. ], 2007: 235-246.
  • 7NIE Zaiqing, MA Yunxiao, SHI Shuming, et al. Web object retrieval [C]//Proceedings of the 16th International Conference on World Wide Web ( WWW 2007 ). New York: ACM Press, 2007 : 81-90.
  • 8NIE Zaiqing, ZHANG Yuanzhi, WEN Jirong, et al. Object-level ranking : bringing order to Web objects [ C ]// Proceedings of the 14th International Conference on World Wide Web (WWW 2005). New York: ACM Press, 2005 : 567-574.
  • 9GUO Jiafeng, XU Gu, CHENG Xueqi, et al. Named en- tity recognition in query [C]//Proceeding of the 32rd In- ternational ACM SIGIR Conference on Research and Development in Information Retrieval ( SIGIR 2009 ). New York: ACM Press, 2009:267-274.
  • 10Klaus Berberich, Srikanta J Bedathur, Thomas Neu- mann, et al. A time machine for text search[C]//Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Informa- tion Retrieval ( SIGIR 2007 ). New York: ACM Press, 2007:519-526.

同被引文献3

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部