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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 莊裕澤(Yuh-Jzer Joung) | |
dc.contributor.author | Ru-Chi Tseng | en |
dc.contributor.author | 曾茹琦 | zh_TW |
dc.date.accessioned | 2021-06-13T00:21:26Z | - |
dc.date.available | 2007-07-31 | |
dc.date.copyright | 2007-07-31 | |
dc.date.issued | 2007 | |
dc.date.submitted | 2007-07-27 | |
dc.identifier.citation | [1] Blogml. http://www.blogml.com/.
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In Proceedings of the First International Conference on Service Oriented Computing (ICSOC 2003), volume 2910 of Lecture Notes in Computer Science, pages 28-42. Springer-Verlag, 2003. [14] Paolo Avesani, Marco Cova, Conor Hayes, and Paolo Massa. Learning contextualised weblog topics. In Proceedings of the second Annual Workshop on the Weblogging Ecosystem: Aggregation, Analysis and Dynamics (WWE 2005), 2005. [15] Ricardo Baeza-Yates and Berthier Ribeiro-Neto. Modern information retrieval. Addison Wesley Longman Publishing Co. Inc., 1999. [16] Grigory Begelman, Philipp Keller, and Frank Smadja. Automated tag clustering: Improving search and exploration in the tag space. In Proceedings of the first workshop on Collaborative Web Tagging at WWW2006, 2006. [17] Tim Berners-Lee, James Hendler, and Ora Lassila. The Semantic Web: A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities, pages 34-43. Scienti‾c American, May 2001. [18] Ulrik Brandes. A faster algorithm for betweenness centrality. Journal of Mathematical Sociology, 25(2):163-177, 2001. [19] Christopher H. Brooks and Nancy Montanez. Improved annotation of the blogosphere via autotagging and hierarchical clustering. In Proceedings of the Fifteenth international conference on World Wide Web (WWW 2006), pages 625-632, New York, NY, United States, 2006. ACM Press. [20] Steve Cayzer. Semantic blogging and decentralized knowledge management. Communications of the ACM, 47(12):47-52, 2004. [21] Alvin Chin and Mark Chignell. A social hypertext model for finding community in blogs. In Proceedings of the seventeenth conference on Hypertext and hypermedia (HYPERTEXT 2006), pages 11-22, New York, NY, United States, 2006. ACM Press. [22] Lilia Efimova, Stephanie Hendrick, and Anjo Anjewierden. Finding 'the life between buildings': An approach for defining a weblog community. In Internet Research 6.0: Internet Generations. Association of Internet Researchers, October 2005. [23] Linton C. Freeman. A set of measures of centrality based on betweenness. Sociometry, 40(1):35-41, March 1977. [24] Linton C. Freeman. Centrality in social networks conceptual clarification. Social Networks, 1(3):215-239, 1979. [25] Ko Fujimura, Takafumi Inoue, and Masayuki Sugisaki. The eigenrumor algorithm for ranking blogs. In Proceedings of the second Annual Workshop on the Weblogging Ecosystem: Aggregation, Analysis and Dynamics (WWE 2005), 2005. [26] Tomohiro Fukuhara, Toshihiro Murayama, and Toyoaki Nishida. Analyzing concerns of people using weblog articles and real world temporal data. In Proceedings of the second Annual Workshop on the Weblogging Ecosystem: Aggregation, Analysis and Dynamics (WWE 2005), 2005. [27] Michelle Girvan and M. E. J. Newman. Community structure in social and biological networks. Proceedings of the National Academy of Sciences of the United States of America, 99(12):7821-7826, 2002. [28] Paul Heymann and Hector Garcia-Molina. Collaborative creation of communal hierarchical taxonomies in social tagging systems. Technical report, Stanford University, October 2006. [29] Digg Inc. Digg. http://digg.com/. [30] David R. Karger and Dennis Quan. What would it mean to blog on the semantic web? In Proceedings of the Third International Semantic Web Conference (ISWC 2004), volume 3298 of Lecture Notes in Computer Science, pages 214{228. Springer-Verlag, 2004. [31] Ravi Kumar, Jasmine Novak, Prabhakar Raghavan, and Andrew Tomkins. On the bursty evolution of blogspace. In Proceedings of the Twelfth international conference on World Wide Web (WWW 2003), pages 568-576, New York, NY, United States, 2003. ACM Press. [32] Robert C. Miller and Krishna Bharat. WebSPHINX: A personal, customizable web crawler. http://www.cs.cmu.edu/~rcm/websphinx/. [33] Knud Möller, John Breslin, and Stefan Decker. semiBlog-Semantic Publishing of Desktop Data. 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In Proceedings of the second Annual Workshop on the Weblogging Ecosystem: Aggregation, Analysis and Dynamics (WWE 2005), 2005. [38] Duncan J. Watts and Steven H. Strogatz. Collective dynamics of 'small-world' networks. Nature, 393:440, June 1998. [39] Tzu-Hsien Yu. Automatic organization of user-generated tags from the web. Master's thesis, National Taiwan University, 2006. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/28762 | - |
dc.description.abstract | 本篇論文藉由引用連結群聚來自不同部落格的相似標記,提供新方法來協助跨部落格的瀏覽。
部落格系統間無法互相溝通,而跨部落格的搜尋及瀏覽成為一項待解議題。部落格中所定義的標記指出部落客所屬的社群面向。因此,群聚相似的標記可以協助部落格間的搜尋瀏覽並區別不同種類的社群。 我們轉化引用連結及文章內容的資訊為圖形,並實驗了一些圖形分群方法。我們也檢驗傳統用文章內容為資訊的聚合階層式分群方法以更全面比較其中差異。 實驗結果顯示,當分群分得較粗時,使用引用資訊做不同部落格間的標記分群與使用內容為資訊的結果相近,但是當分群分得較細時,使用引用資訊的結果會比較好一些。然而,處理文章內容的資料較為費力,所以引用連結分析是一項輕量且有效的標記分群及協助跨部落格瀏覽的方法。 | zh_TW |
dc.description.abstract | In this thesis, we utilize the citation links to cluster similar tags from different blogs together to provide a new way to assist cross-blog browsing.
Since blog systems could not communicate with each other, cross-blog searching and browsing is an issue to be solved. Tags defined in a blog indicate the aspects of communities the blogger belongs to. Thus, clustering similar tags together might help searching and browsing across blogs and distinguishing di?erent types of communities. We transform the citation and content information to create graphs and experiment several graphical clustering methods. We also examine the traditional agglomerative hierarchical clustering methods using the information of content to have a thorough comparison. The experiment result shows that clustering tags from blogs by the information of citation has roughly the same performance compared with clustering by the information of content in lower granularity and outperforms a little bit in higher granularity. However, it requires much more e?orts to process the data of content. Thus, citation link analysis is a light-weight and effective method to cluster tags and to assist cross-blog browsing. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T00:21:26Z (GMT). No. of bitstreams: 1 ntu-96-R94725033-1.pdf: 424337 bytes, checksum: effa86c60983de96cab3c6a7e2719cdc (MD5) Previous issue date: 2007 | en |
dc.description.tableofcontents | 1 Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.4 Thesis Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2 Related Work 5 2.1 Mechanisms Assisting Cross-Blog Searching and Browsing . . . . . . . 5 2.1.1 Changing the Structure of Blog Systems . . . . . . . . . . . . . 5 2.1.2 Mapping Tags Among Blogs . . . . . . . . . . . . . . . . . . . . 6 2.1.2.1 Folksonomy Mapping . . . . . . . . . . . . . . . . . . . 7 2.1.2.2 Machine Mapping . . . . . . . . . . . . . . . . . . . . 8 2.1.3 Brief Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.2 Tag Clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3 System Design 10 3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.2 Graphical Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.2.1 Citation Graph . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.2.2 Content Graph . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.3 Clustering Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3.3.1 Graphical Clustering Methods . . . . . . . . . . . . . . . . . . . 13 3.3.1.1 Edge Betweenness . . . . . . . . . . . . . . . . . . . . 13 3.3.1.2 Common Neighbors . . . . . . . . . . . . . . . . . . . 14 3.3.1.3 k-core Decomposition . . . . . . . . . . . . . . . . . . 15 3.3.2 Hierarchical Content Clustering Methods . . . . . . . . . . . . . 15 3.3.2.1 Single Linkage . . . . . . . . . . . . . . . . . . . . . . 16 3.3.2.2 Complete Linkage . . . . . . . . . . . . . . . . . . . . 16 3.3.2.3 Average Linkage . . . . . . . . . . . . . . . . . . . . . 16 3.3.2.4 Centroid Linkage . . . . . . . . . . . . . . . . . . . . . 16 4 Experiment Results and Discussion 18 4.1 Data Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 4.1.1 Crawled Data Description . . . . . . . . . . . . . . . . . . . . . 18 4.1.2 Data Pruning . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 4.1.3 Analysis of Tag Groups . . . . . . . . . . . . . . . . . . . . . . . 20 4.2 Evaluation Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4.3 Experiment Results and Comparison . . . . . . . . . . . . . . . . . . . 25 4.3.1 Results of Graphical Clustering Methods . . . . . . . . . . . . . 25 4.3.1.1 Results of Edge Betweenness . . . . . . . . . . . . . . 25 4.3.1.2 Results of Common Neighbors . . . . . . . . . . . . . . 26 4.3.1.3 Results of k-core . . . . . . . . . . . . . . . . . . . . . 29 4.3.1.4 Brief Summary of Graphical Clustering Results . . . . 31 4.3.2 Results of Agglomerative Hierarchical Content Clustering Methods 32 4.3.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 5 Conclusion and Future Work 36 5.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 5.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Bibliography 38 | |
dc.language.iso | en | |
dc.title | 由文章分類和引用關係改善跨部落格瀏覽機制 | zh_TW |
dc.title | Improving Cross-Blog Browsing Mechanism by Classification and Citation | en |
dc.type | Thesis | |
dc.date.schoolyear | 95-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 李瑞庭(Anthony J.T. Lee),蔡益坤(Yih-Kuen Tsay),陳炳宇(Bin-Yu Chen) | |
dc.subject.keyword | 部落格,連結分析,標記分群,資料分群,社會網絡分析, | zh_TW |
dc.subject.keyword | Blog,Link Analysis,Tag Clustering,Data Clustering,Social Network Analysis, | en |
dc.relation.page | 41 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2007-07-27 | |
dc.contributor.author-college | 管理學院 | zh_TW |
dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
顯示於系所單位: | 資訊管理學系 |
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