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现代图书情报技术  2012, Vol. 28 Issue (7): 76-81     https://doi.org/10.11925/infotech.1003-3513.2012.07.12
  知识组织与知识管理 本期目录 | 过刊浏览 | 高级检索 |
基于关键词链的动态分面研究
王莉
中国科学技术信息研究所 北京 100038
Dynamic Faceted Method Based on Keyword Chains
Wang Li
Institute of Scientific & Technical Information of China, Beijing 100038, China
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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。
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王莉
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    
Abstract:This paper proposes a dynamic faceted method based on formal concept analysis, which extracts author keywords 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.
Key wordsKeyword chains    Dynamic faceted method    Formal concept analysis    Concept lattice    Semantic similarity
收稿日期: 2012-07-16      出版日期: 2012-10-11
: 

TP391

 
基金资助:

本文系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。

引用本文:   
王莉. 基于关键词链的动态分面研究[J]. 现代图书情报技术, 2012, 28(7): 76-81.
Wang Li. Dynamic Faceted Method Based on Keyword Chains. New Technology of Library and Information Service, 2012, 28(7): 76-81.
链接本文:  
https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2012.07.12      或      https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2012/V28/I7/76
[1] 李伯阳.文本聚类方法研究及其应用[D].厦门:厦门大学,2008.(Li Boyang. Research on Text Clustering Methods and Their Applications [D]. Xiamen:Xiamen University, 2008.)

[2] Priss U. Faceted Information Representation[C]. In:Proceedings of the 8th International Conference on Conceptual Structures. Germany:Shaker Verlag Aachen, 2000:84-94.

[3] Kashyap A, Hristidis V, Petropoulos M, et al. Effective Navigation of Query Results Based on Concept Hierarchies [J]. IEEE Transactions on Knowledge and Data Engineering, 2011, 23(4):540-553.

[4] Ling X, Mei Q Z, Zhai C X, et al. Mining Multi-faceted Overviews 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.

[5] Krohn U, Davies N J, Weeks R. Concept Lattices for Knowledge Management [J]. BT Technology Journal, 1999,17(4):108-116.

[6] Koren J, Zhang Y, Liu X. Personalized Interactive Faceted Search [C]. In:Proceedings of the 17th International Conference on World Wide Web(WWW’08). New York:ACM Press, 2008:477-486.

[7] Ben-Yitzhak O, Golbandi N, Har’EI N, et al. Beyond Basic Faceted Search [C]. In:Proceedings of the International Conference on Web Search and Web Data Mining(WSDM’ 08). New York:ACM Press, 2008:33-44.

[8] Dash D, Rao J, Meqiddo N, et al. Dynamic Faceted Search for Discovery-driven Analysis [C]. In:Proceedings of the 17th International Conference on Information and Knowledge Management(CIKM’08). New York:ACM Press, 2008:3-12.

[9] 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):1590-1602. (He Chao, Cheng Xueqi, Guo Jiafeng. Mining Hierarchical Concept Lattice for Faceted Navigation [J]. Chinese Journal of Computers, 2011, 34(9):1590-1602.)

[10] 赵金海.基于分面主题图探索式搜索研究[J]. 情报杂志 ,2012,31(1):175-179. (Zhao Jinhai. Research on the Facet-based Exploratory Search in Topic Maps [J]. Journal of Intelligence, 2012, 31(1):175-179.)

[11] Kuo B Y-L, Hentrich T,Good B M, et al. Tag Clouds for Summarizing Web Search Results [C]. In:Proceedings of the 16th International Conference on World Wide Web(WWW’07).New York:ACM Press, 2007:1203-1204.

[12] Dachselt R, Frisch M, Weiland M. FacetZoom:A Continuous Multi-scale Widget for Navigating Hierarchical Metadata [C]. In:Proceedings of the 26th Annual SIGCHI Conference on Human Factors in Computing Systems(CHI’08). New York:ACM Press, 2008:1353-1356.

[13] Karlson A K, Robertson G G, Robbins D C, et al. FaThumb:A Facet-based Interface for Mobile Search [C]. In:Proceedings of the 24th Annual SIGCHI Conference on Human Factors in Computing Systems(CHI’06). New York:ACM Press, 2006:711-720.

[14] 罗式胜.篇名关键词链特征的统计分析及应用[J]. 中国图书馆学报 ,1995,21(1):27-29. (Luo Shisheng. The Statiscal Analysis of the Characteristics of Title Keywords [J]. Journal of Library Science in China, 1995,21(1):27-29.)

[15] 裴婧,包宏.汉语句子相似度计算在FAQ中的应用[J]. 计算机工程 ,2009,35(17):46-48. (Pei Jing, Bao Hong. Application of Chinese Sentence Similarity Computation in FAQ [J]. Computer Engineering, 2009,35(17):46-48.)

[16] 何娟,高志强,陆青健,等.基于词汇相似度的元素级本体匹配[J]. 计算机工程 ,2006,32(16):185-187. (He Juan, Gao Zhiqiang, Lu Qingjian, et al. Element Level Ontology Matching Based on Lexical Similarity [J]. Computer Engineering, 2006, 32(16):185-187.)

[17] Wu Z, Palmer M. Verb Semantics and Lexical Selection [C]. In:Proceedings of the 32nd Annual Meeting on Association for Computational Linguistics(ACL’94). Stroudsburg:Association for Computational Linguistics,1994:133-138.

[18] 刘宇鹏,李生,赵铁军.基于WordNet词义消歧的系统融合[J]. 自动化学报 , 2010,36(11):1575-1580. (Liu Yupeng, Li Sheng, Zhao Tiejun. System Combination Based on WSD Using WordNet [J]. Acta Automatica Sinica, 2010, 36(11):1575-1580.)

[19] 谢彩霞,梁立明,王文辉.我国纳米科技论文关键词共现分析[J]. 情报杂志 ,2005,24(3):69-73. (Xie Caixia, Liang Liming, Wang Wenhui. Co-Keyword Analysis in the Filed of Nanotechnology in China [J]. Journal of Intelligence,2005,24(3):69-73.)

[20] Agirre E, Rigau G. A Proposal for Word Sense Disambiguation Using Conceptual Distance [C]. In:Proceedings of International Conference on Recent Advances in Natural Language Processing(RANLP’95),Tzigov Chark.1995.

[21] Priss U E. A Graphical Interface for Document Retrieval Based on Formal Concept Analysis[C]. In:Proceedings of the 8th Midwest Artificial Intelligence and Cognitive Science Conference. 1997:66-70.
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