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基于关键词链的动态分面研究 被引量：1

Dynamic Faceted Method Based on Keyword Chains
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摘要 从关键词链入手,结合形式概念分析技术,提出一种基于关键词链的动态分面方法。该方法首先采用作者关键词描述文献,然后基于相似度计算判断并合并语义上几乎一致的关键词,形成粗细不同粒度的形式背景,最后利用格技术构造搜索结果的语义分面。实证分析证明该方法可行、有效。 This paper proposes a dynamic faceted method based on formal concept analysis, which extracts author key- words of literature, then merges the semantic similar keywords based on similarity calculation, and generates different granularity formal contexts. Finally, a lattice -based semantic faceted navigation is given. The empirical analysis shows that the method is feasible and effective.
作者 王莉
机构地区 中国科学技术信息研究所
出处 《现代图书情报技术》 CSSCI 北大核心 2012年第7期76-81,共6页 New Technology of Library and Information Service
基金 国家十二五科技支撑计划项目"信息资源自动处理 智能检索与STKOS应用服务集成"(项目编号:2011BHA10B05)的研究成果之一
关键词 关键词链 动态分面方法 形式概念分析 概念格 语义相似度 Keyword chains Dynamic faceted method Formal concept analysis Concept lattice Semantic simi- larity
分类号 TP391.1 [自动化与计算机技术—计算机应用技术]
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参考文献20

  • 1Priss U. Faceted Information Representation [ C ]. In : Proceedings of the Sth International Conference on Conceptual Structures. Ger- many : Shaker Verlag Aachen, 2000 : 84 - 94.
  • 2Kashyap A, Hristidis V, Pctropoulos M, et al. Effective Navigation of Query Results Based on Concept Hierarchies [J]. IEEE Trans- actions on Knowledge and Data Engineering, 2011, 23(4) :540 - 553.
  • 3Ling X, Mei Q Z, Zhai C X, et al. Mining Multi - faceted Over- views of Arbitrary Topics in a Text Collection [ C ]. In : Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining ( KDD' 08 ). New York : ACM Press, 2008:497 - 505.
  • 4Krohn U, Davies N J, Weeks R. Concept Lattices for Knowledge Management [J]. BT Technology Journal, 1999,17(4) : 108 - 116.
  • 5Koren J, Zhang Y, Liu X. Personalized Interactive Faceted Search [ C]. In:Proceedings of the 17th International Conference on World Wide Web(WWW'0$). New York:ACM Press, 2008:477 -486.
  • 6Ben-Yitzhak O, Golbandi N, Har' El N, et al. Beyond Basic Faceted Search [ C ]. In : Proceedings of the International Confer- ence on Web Search and Web Data Mining ( WSDM' 08 ). New York : ACM Press, 2008:33 - 44.
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  • 8何超,程学旗,郭嘉丰.面向分面导航的层次概念格模型及挖掘算法[J].计算机学报,2011,34(9):1589-1602. 被引量：9
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二级参考文献70

  • 1王常亮,滕至阳.语句相似度计算在FAQ中的应用[J].计算机时代,2006(2):24-26. 被引量：10
  • 2Bergman M K. The deep web: Surfacing hidden value. Jour nal of Electronic Publishing, 2001, 7(1) : 113-153.
  • 3Kashyap A, Hristidis V, Petropoulos M. FACeTOR: Cost- driven exploration of faeeted query results//Proceedings of the 17th International Conference Information and Knowl- Edge Management (CIKM' 10). Toronto, Ontario, Canada, 2010:719-728.
  • 4Hearst M. Clustering versus faceted categories for informa- tion exploration. Communications of the ACM, 2006, 49(4) : 59-61.
  • 5Roy S B et al. Minimum effort driven dynamic faceted search in structured databases//Proceedings of the 17th Internation- al Conference on Information and Knowl-Edge Management (CIKM'08). Napa Valley, California, USA, 2008:13-22.
  • 6Roy S Bet al. DynaCet : Building dynamic faceted search sys- tems over databases//Proceedings of the 25th International Conference on Data Mining (ICDE' 09). Shanghai, China, 2009:1463-1466.
  • 7Kashyap A et al. Exploring biomedical databases with BioNav //Proceedings of the 28th ACM SIGMOD International Con- ference on Management of Data (SIGMODJ09). Providence, Rhode Island, USA, 2009:1079-1082.
  • 8Kashyap A, Hristidis V, Petropoulos M, Tavoulari S. Effective navigation of query results based on concept hierar chies. IEEE Transactions on Knowledge and Data Engineer ing, 2011, 23(4): 540-553.
  • 9Koren J, Zhang Y, Liu X. Personalized interactive faceted search//Proceedings of the 17th International Conference on World Wide Web(WWW'08). Beijing, China, 2008: 477- 486.
  • 10Ben-Yitzhak O et al. Beyond basic faceted search//Proceed- ings of the International Conference on Web Search and Web Data Mining (WSDM' 08). Palo Alto, California, USA, 2008:33-44.

共引文献163

同被引文献21

引证文献1

二级引证文献7

现代图书情报技术
2012年 第7期

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