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一种基于偏好的查询扩展方法 被引量：1

A query expansion scheme based on user profiles
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摘要 为克服语言歧义性和用户使用简短查询语句的习惯对搜索引擎查询准确率造成的影响,提出了一种基于偏好的查询扩展方法。该方法将用户对网页的偏好转化为对知识库中概念的偏好,建立用户兴趣模型,在该模型基础上对原始查询结果进行分析,挑选出与用户偏好关联最紧密的关键词加入原查询,解决了基于局部分析的查询扩展方法在初次检索质量不高时性能恶化的问题。实验表明,本文提出的方法相对于传统的查询扩展算法可以大幅度提高查询精度。 To solve the problems of polysemy and short query that affect the precision of the search engines, this paper proposes a query expansion scheme based on user profiles. This schema gains the users＇ interests in web pages, and classifies these web pages into conceptions in knowledge base to create user profiles about users＇ interests in these conceptions： Based on user profiles, the terms which are most related to user interests are selected as expansion terms. This scheme can overcome the drawback of local analysis that the effects of expanded query strongly depend on the quality of the initial retrieval. The experimental results show that the proposed query expansion scheme can achieve significant improvements in retrieval effectiveness compared to current query expansion techniques.
作者 梅翔 陈俊亮 徐萌
机构地区 北京邮电大学网络与交换技术国家重点实验室
出处 《高技术通讯》 CAS CSCD 北大核心 2007年第11期1142-1146,共5页 Chinese High Technology Letters
基金 863计划（2002AA121012）、国家自然科学基金（60432010）和973计划（2003CB314806）资助项目.
关键词 信息检索 个性化 查询扩展 用户日志 偏好 搜索引擎 information retrieval, personalization, query expansion, user log
分类号 TP393 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献12

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二级参考文献41

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共引文献393

同被引文献14

  • 1Nicholas J.Belkin.Some (what) challenges and grand challenges for information retrieval[J].ACM SIGIR Forum,2008,42(1):47-54.
  • 2Jing Bai,Jian-Yun Nie,Guihong Cao,Hugues Bouchard.Using query contexts in information retrieval[C]//Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval.2007:15-22.
  • 3Xuehua Shen,Bin Tan,ChengXiang,Zhai.Implicit user modeling for personalized search[C]//Proceedings of the 14 th ACM international conference on Information and knowledge management.2005:824-831.
  • 4Yuanhua Lv,Le Sun,Junlin Zhang,Jian-Yun Nie Wan Chen,Wei Zhang.An iterative implicit feedback approach to personalized search[C]//Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics.2006:585-592.
  • 5Sugiyama K,Hatano K,K Yoshikawa M.Adaptive web search based on user profile constructed without any effort from users[C]//Proceedings of the 13th international conference on World Wide Web.2003:675-684.
  • 6Susan Gauch,Jason Chaffee,Alaxander Pretschner.Ontology-based personalized search and browsing[J],Web Intelligence and Agent Systems.2003,1(3-4):219-234.
  • 7Teevan,J.,Dumais,S.T.,& Horvitz,E.(2005).Personalizing search via automated analysis of interests and activites[C]//Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval,2005:449-456.
  • 8Bin Tan,Xuehua Shen,ChengXiang Zhai.Mining long-term search history to improve search accuracy[C]//Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining,2006:718-723.
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  • 10Jinxi Xu,W.Bruce Croft.Improving the effectiveness of information retrieval with local context analysis[J].ACM Transactions on Information Systems (TOIS).2000,18(1):79-112.

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二级引证文献12

高技术通讯
2007年 第11期

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