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现代图书情报技术  2012, Vol. 28 Issue (5): 32-40    DOI: 10.11925/infotech.1003-3513.2012.05.05
  知识组织与知识管理 本期目录 | 过刊浏览 | 高级检索 |
基于向心扩散加权XML模型的异构用户个性化模式匹配方法
李树青, 刘晓倩
南京财经大学信息工程学院 南京 210046
The Matching Algorithm of Heterogeneous User Personalized Profile Based on Centripetal Spreading Weighted XML Model
Li Shuqing, Liu Xiaoqian
College of Information Engineering, Nanjing University of Finance & Economics, Nanjing 210046, China
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摘要 介绍一种利用同文词语共现和引文词语共现分析实现的领域本体自动构建方法,该本体采用加权XML模型,利用概念联系中的权值设定可以有效地表达用户兴趣程度的差异,并利用基于向心扩散的扩散激活方法对用户兴趣特征及其联系提供更强的表达能力,以便于发现更有价值的潜在用户兴趣。进而介绍如何利用该本体按照“先打碎后重构”的策略将异构用户个性化模式转换为可以进行比较的一致模式,并对相关的异构用户个性化模式匹配方法做出详细说明。最后总结相关测试实验及其结果。
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李树青
刘晓倩
关键词 领域本体加权XML个性化词语共现分析    
Abstract:This paper introduces an automatic construction method for domain Ontology implemented by words co-occurrence analysis in both document and citation. This Ontology adopts weighted XML model and uses weight in concepts and their relationship to express the difference of users' interest effectively,which can improve the ability of expressing users' interest and their relationship with centripetal weight spreading activation strategy in order to explore more valuable users' interest. Meantime, this paper also discusses how to use this Ontology to transform heterogeneous user personalized profile to consistent comparable model with the broken-and-reconstruction strategy, and how to match corresponding heterogeneous user personalized profile in detail. Finally, the result of correlative tests and experiments are concluded.
Key wordsDomain Ontology    Weighted XML    Personalization    Words co-occurrence analysis
收稿日期: 2012-04-24     
: 

G202

 
基金资助:

本文系国家自然科学基金项目“基于通用加权XML模型的个性化用户兴趣本体研究”(项目编号:71103081)和江苏省高校自然科学研究面上资助项目“通用加权XML模型在便携式个性化用户兴趣本体中的表达方法研究”(项目编号:11KJB630001)的研究成果之一。

引用本文:   
李树青, 刘晓倩. 基于向心扩散加权XML模型的异构用户个性化模式匹配方法[J]. 现代图书情报技术, 2012, 28(5): 32-40.
Li Shuqing, Liu Xiaoqian. The Matching Algorithm of Heterogeneous User Personalized Profile Based on Centripetal Spreading Weighted XML Model. New Technology of Library and Information Service, DOI:10.11925/infotech.1003-3513.2012.05.05.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2012.05.05
[1] 李树青.基于加权XML数据模型的个性化本体研究[J]. 情报学报 ,2010,29(5):826-834.(Li Shuqing.Study of Personalized Ontology Based on Weighted XML Data Model[J].Journal of the China Society for Scientific and Technical Information,2010,29(5):826-834.)

[2] Tamine-Lechani L,Boughanem M,Zemirli N.Personalized Document Ranking: Exploiting Evidence from Multiple User Interests for Profiling and Retrieval[J].Journal of Digital Information Management,2008,6(5):354-361.

[3] Liu F,Yu C,Meng W Y.Personalized Web Search for Improving Retrieval Effectiveness[J].IEEE Transactions on Knowledge and Data Engineering,2004,16(1):28-40.

[4] Gauch S,Chaffee J,Pretschner A.Ontology-based Personalized Search and Browsing[J].Web Intelligence and Agent System,2003,1(3-4):219-234.

[5] Sieg A,Mobasher B,Burke R.Web Search Personalization with Ontological User Profiles[C].In:Proceedings of the 16th ACM Conference on Information and Knowledge Management(CIKM'07).New York, NY, USA:ACM,2007:525-534.

[6] Gabrilovich E,Markovitch S.Computing Semantic Relatedness Using Wikipedia-based Explicit Semantic Analysis[C].In: Proceedings of the 20th International Joint Conference on Artificial Intelligence.2007:12-18.

[7] Vallet D, Cantador I, Fernández M, et al. A Multi-purpose Ontology-based Approach for Personalized Content Filtering and Retrieval[C]. In: Proceedings of the 1st International Workshop on Semantic Media Adaptation and Personalization.2006:19-24.

[8] 颜端武,刘明岩,许应楠.基于领域本体的细粒度用户兴趣建模研究[J]. 情报学报 ,2010,29(3):433-442.(Yan Duanwu,Liu Mingyan,Xu yingnan.Toward Fine-grained User Preference Modeling Based on Domain Ontology[J].Journal of the China Society for Scientific and Technical Information,2010,29(3):433-442.)

[9] Bhattacharyya P,Garg A,Wu S F.Analysis of User Keyword Similarity in Online Social Networks[J].Social Network Analysis and Mining,2011,1(3):143-158.

[10] 刘萍,叶燕.基于本体的高校专家定位系统研究[J]. 情报学报 ,2010,29(5):813-819.(Liu Ping,Ye Yan.An Ontology-based Experts Locator System Within Academia[J].Journal of the China Society for Scientific and Technical Information,2010,29(5):813-819.)

[11] Stuckenschmidt H,Harmelen F.Information Sharing on the Semantic Web[M].Springer,2005:3-4.

[12] Mao M,Peng Y F,Spring M.An Adaptive Ontology Mapping Approach with Neural Network Based Constraint Satisfaction[J].Web Semantics: Science, Services and Agents on the World Wide Web,2010,8(1):14-25.

[13] Ehrig M.Ontology Alignment:Bridging the Semantic Gap(Semantic Web and Beyond)[M].Springer,2006:1-2.

[14] Mao M.Ontology Mapping:An Information Retrieval and Interactive Activation Network Based Approach[C].In: Proceedings of the 6th International Semantic Web and the 2nd Asian Conference on Asian Semantic Web Conference.2007:931-935.

[15] Mao M,Peng Y F,Spring M.Ontology Mapping: As a Binary Classification Problem[C].In: Proceedings of the 4th International Conference on Semantics, Knowledge and Grid.2008:20-25.

[16] Koren Y,Park F.Factorization Meets the Neighborhood: A Multifaceted Collaborative Filtering Model[C].In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.New York, NY, USA:ACM,2008:426-434.

[17] Haase P,Hotho A,Schmidt-Thieme L,et al.Collaborative and Usage-driven Evolution of Personal Ontologies[C]. In: Proceedings of the 2nd European Conference on the Semantic Web: Research and Applications.2005:486-499.

[18] 邓珞华.概念空间——定义、意义和局限[J]. 情报学报 ,2003,22(4):393-397.(Deng Luohua.Concept Space——Its Definition,Significance and Limitation[J].Journal of the China Society for Scientific and Technical Information,2003,22(4):393-397.)

[19] 吕刚,郑诚.基于加权的本体相似度计算方法[J]. 计算机工程与设计 ,2010,31(5):1093-1095.(Lv Gang,Zheng Cheng.Method of Ontology Similarity Calculation Based on Weighted [J].Computer Engineering and Design,2010,31(5):1093-1095.)

[20] Tsatsaronis G,Vazirgiannis M,Androutsopoulos I.Word Sense Disambiguation with Spreading Activation Networks Generated from Thesauri[C].In: Proceedings of the 20th International Joint Conference on Artificial Intelligence.2007:1725-1730.

[21] Rocha C,Schwabe D,Aragao M P.A Hybrid Approach for Searching in the Semantic Web[C].In: Proceedings of the 13th International Conference on World Wide Web. New York, NY, USA:ACM,2004:374-383.

[22] Middleton S E,Shadbolt N R,De Roure D C.Ontological User Profiling in Recommender Systems[J].ACM Transactions on Information Systems,2004,22(1):54-88.

[23] Thiagarajan R,Manjunath G,Stumptner M.Computing Semantic Similarity Using Ontologies[R].HP Labs Technical Report,HPL-2008-87,2008.

[24] Sieg A,Mobasher B,Burke R.Improving the Effectiveness of Collaborative Recommendation with Ontology-based User Profiles[C].In: Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems (HetRec '10).New York, NY, USA:ACM,2010:39-46.

[25] 李树青,徐侠,钱钢,等.基于震荡算法和领域本体的学术文献关键路径自动识别和可视化展示方法[J]. 情报学报 ,2012,待发.(Li Shuqing,Xu Xia,Qian Gang,et al.An Automatic Recognition and Visualization Method of Main-path in Academic Documents Based on Vibration Algorithm and Domain Ontology[J].Journal of the China Society for Scientific and Technical Information,2012,Accepted.)

[26] Zhou T,Kuscsik Z,Liu J G,et al.Solving the Apparent Diversity-accuracy Dilemma of Recommender Systems[J]. Proceedings of the National Academy of Sciences(PNAS),2010, 107(10): 4511-4515.

[27] Daoud M,Tamine-Lechani L,Boughanem M,et al.A Session Based Personalized Search Using an Ontological User Profile[C].In: Proceedings of the 2009 ACM Symposium on Applied Computing.New York, NY, USA:ACM,2009:1732-1736.

[28] IJntema W,Goossen F,Frasincar F,et al.Ontology-based News Recommendation[C].In:Proceedings of the 2010 EDBT/ICDT Workshops. New York, NY, USA:ACM,2010:16-23.

[29] National Information Standards Organization.Guidelines for the Construction,Format,and Management of Monolingual Controlled Vocabularies[S].Bethesda:NISO Press,2005.

[30] 余传明,张小青.从Wikipedia中获取本体:原理与方法研究[J]. 情报学报 ,2011,30(3):244-252.(Yu Chuanming,Zhang Xiaoqing.Learning Ontology from Wikipedia :Principles and Methods[J].Journal of the China Society for Scientific and Technical Information,2011,30(3):244-252.)

[31] 薛建武,勾苗,吴拓.基于SKOS的国防科学技术叙词表向本体的转换研究[J]. 情报学报 ,2011,30(3):310-317.(Xue Jianwu,Gou Miao,Wu Tuo.The Transformation from Thesaurus of National Defense Science and Technology to Ontology Based on SKOS[J].Journal of the China Society for Scientific and Technical Information,2011,30(3):310-317.)

[32] 冯璐,冷伏海.共词分析方法理论进展[J]. 中国图书馆学报 ,2006,32(2):88-92.(Feng Lu,Leng Fuhai.Development of Theoretical Studies of Co-Word Analysis[J].Journal of Library Science in China,2006,32(2):88-92.)

[33] 李枫林,何洲芳.基于关键词共现分析的检索结果聚类研究[J]. 情报学报 ,2011,30(8):819-825.(Li Fenglin,He Zhoufang .Study on Clustering of Retrieval Results Based on Co-occurrence Analysis of Keywords[J].Journal of the China Society for Scientific and Technical Information,2011,30(8):819-825.)

[34] 杨颖,崔雷.基于共词可视化的学科战略情报研究[J]. 情报学报 ,2011,30(3):325-330.(Yang Ying,Cui Lei.Subject Strategic Information Research Based on Visualization of Co-Word Network[J].Journal of the China Society for Scientific and Technical Information,2011,30(3):325-330.)

[35] 王胜君,吴冲,张新颖,等.基于共现分析的专利地图绘制及实证研究——一个政府信息重构的视角[J]. 情报学报 ,2011,30(3):318-324.(Wang Shengjun,Wu Chong,Zhang Xinying,et al.Patent Map Drawing and Its Application of Based on Co-occurrence Analysis:Perspective of Government Information Restructuring[J].Journal of the China Society for Scientific and Technical Information,2011,30(3):318-324.)

[36] 杜慧平.概念等级关系自动识别研究[J]. 情报学报 ,2011,30(3):237-243.(Du Huiping.Automatic Extraction of Concept Hierarchical Relationships[J].Journal of the China Society for Scientific and Technical Information,2011,30(3):237-243.)

[37] 李树青.基于引文关键词加权共现技术的图情学科领域本体自动构建方法研究[J]. 情报学报 ,2012,31(4):371-380.(Li Shuqing.Research of Automatic Construction of Domain Ontology in Library and Information Science Based on Weighted Co-occurrence of Citation Keywords[J].Journal of the China Society for Scientific and Technical Information,2012,31(4):371-380.)

[38] 张学福.基于词共现的可视化概念空间研究[J]. 情报学报 ,2008,27(2):205-211.(Zhang Xuefu.Research on Visualization Concept Space Based on Co-word Occurrence[J].Journal of the China Society for Scientific and Technical Information,2008,27(2):205-211.)

[39] Pedersen T,Pakhomov S V S,Patwardhan S,et al.Measures of Semantic Similarity and Relatedness in the Biomedical Domain[J].Journal of Biomedical Informatics,2007,40(3):288-299.

[40] 董慧,唐敏.语义检索在Web2.0环境下的应用探讨[J]. 中国图书馆学报 ,2011,37(2):115-119.(Dong Hui,Tang Min.Application of Semantic Search in the Web2.0 Environment[J].Journal of Library Science in China,2011,37(2):115-119.)

[41] Rada R,Mili H,Bichnell E,et al.Development and Application of a Metric on Semantic Nets[J].IEEE Transactions on System Management and Cybernetics,1989,19(1):17-30.

[42] Cimiano P.Ontology Learning and Population from Text:Algorithms,Evaluation and Applications[M].Springer-Verlag,2006:44-45.

[43] Patwardhan S,Pedersen T.Using WordNet-based Context Vectors to Estimate the Semantic Relatedness of Concepts[C].In: Proceedings of the EACL 2006,Workshop on Making Sense of Sense:Bringing Psycholinguistics and Computational Linguistics Together,Trento,Italy.2006:1-8.

[44] Bollegala D,Matsuo Y,Ishizuka M.WebSim:A Web-based Semantic Similarity Measure[C].In: Proceedings of the 21st Annual Conference of the Japanese Society for Artificial Intelligence(JSAI2007),Miyazaki,Japan.2007:757-766.

[45] Resnik P.Using Information Content to Evaluate Semantic Similarity in a Taxonomy[C]. In: Proceedings of the 14th International Joint Conference on Artificial Intelligence(IJCAI' 95),Montreal,Canada.1995:448-453.

[46] Batet M,Sánchez D,Valls A.An Ontology-based Measure to Compute Semantic Similarity in Biomedicine[J].Journal of Biomedical Information,2011,44(1):118-125.

[47] 温馨,陈群,娄颖.基于词项扩展的XML信息检索反馈技术[J]. 计算机工程 ,2011,37(20):36-38.(Wen Xin,Chen Qun,Lou Ying.Feedback Technique for XML Information Retrieval Based on Term Expansion[J].Computer Engineering,2011,37(20):36-38.)

[48] 韩毅,张克菊,金碧辉.引文网络分析的方法整合研究进展[J]. 中国图书馆学报 ,2010,36(4):83-89.(Han Yi,Zhang Keju,Jin Bihui.Research Progress on Methodology Integration of Citation Network Analysis[J].Journal of Library Science in China,2010,36(4):83-89.)
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