Publications-Theses

題名 在社會網路上透過Tag-Thesaurus模型達到有效的資源彙整
Resource Aggregation via Tag-Thesaurus model on Social Web
作者 宋昆銘
貢獻者 胡毓忠
Hu, Yuh Jong,
宋昆銘
關鍵詞 標籤系統
社會網路服務
語意網
資源彙整
tagging systems
social network service
semantic web
resource aggregation
日期 2007
上傳時間 17-Sep-2009 14:03:14 (UTC+8)
摘要 我們從自然語言領域中借用Thesaurus模型作為字彙關聯的基礎,陸續加入Folksonomy概念、Social Network Service指標的蒐集以及domain-specific ontology來建構Tag-Thesaurus模型,用來解決使用一般tagging system資源彙整能力不足的問題。首先我們對將要實驗的領域選取初始字彙,並利用這些字彙建構Tag-Thesaurus模型。接著將預先準備的這些字彙釋放到社會網路服務平台的tagging system中,透過社會網路服務平台中的tagging system來蒐集使用者對於資源的平面分類資訊,利用這些資訊來對Tag-Thesaurus模型持續地擴充。透過這樣的Tag-Thesaurus模型,我們將可以獲得較佳的資源彙整。domain-specific ontology的加入將可以強化由上而下的資源彙整。而Social Network Service當中的其他資訊,如FOAF[16]或是個人的偏好等,將可以提昇個人化資源彙整的能力。這樣的結合方式不僅是ontology應用的示範,我們更希望透過這樣的混合式模型,使得Web 2.0這樣子廣泛蒐集眾人智慧的概念能夠成為跨入語意網的橋樑。
We aggregate various resources through the Tag-Thesaurus Model. There are three parts in Tag-Thesaurus model, the Folksonomy formal model, indices collection on Social Network Service, and lightweight domain-specific ontology. The Folksnomy model reconstruct relationships between tags, and we can aggregate resources by tags. The indices collection on Social Network Service help us to decide which resource are more important. Finally, the lightweight domain-specific ontology provide the standard interface to describe the relationships between tags.
參考文獻 【1】 Andreas Hotho, Robert J̈aschke, Christoph Schmitz, Gerd Stumme.“Information Retrieval in Folksonomies: Search and Ranking.” The Semantic Web: Research and Applications.
【2】 Alexandre Passant, Jean-David Sta, Philippe Laublet.“Folksonomies, Ontologies and Corporate Blogging.”http:// apassant.net/blog/tag/blogtalkreloaded.
【3】 Andreas Hotho, Robert J¨aschke, Christoph Schmitz,“FolkRank: A Ranking Algorithm for Folksonomies” Proc. FGIR 2006.
【4】 Hongwei Zhu, Michael D. Siegel, Stuart E. Madnick, Pablo Castells.“Information Aggregation – A Value-added E-Service.” Proceedings of the International Conference on Technology, Policy, and Innovation: Critical Infrastructures, The Netherlands, June 26-29, 2001.
【5】 Peter Mika.“Flink: Semantic Web Technology for the Extraction and Analysis of Social Networks.” Journal of Web Semantics(2005).
【6】 Scott A. Golder and Bernardo A. Huberman.“The Structure of Collaborative Tagging Systems.” Arxiv preprint cs.DL/0508082, 2005.
【7】 Thomas Gruber.“Ontology of Folksonomy: A Mash-up of Apples and Oranges.” Invited paper/keynote to the First on-Line conference on Metadata and Semantics Research (MTSR`05).
【8】 Clay Shirky, "Ontology is Overrated: Categories, Links, and Tags", http://www.shirky.com/writings/ontology_overrated.html
【9】 Jakob Voss, "Tagging, Folksonomy & Co-Renaissance of Manual Indexing?", Systems of Knowledge Organization for Digital Libraries:Beyond Traditional Authority files. CLIR Publications, 2000.
【10】 Cameron Marlow, "Position Paper, Tagging, Taxonomy, Flickr, Article, ToRead", Hypertext 2006.
【11】 Scott A. Golder, "Usage patterns of collaborative tagging systems", Journal of Information Science.
【12】 Paul Heymann, "Collaborative Creation of Communal Hierarchical Taxonomies in Social Tagging Systems", Berlin EuroIA Summit 2006.
【13】 Emanuele Quintarelli, "Facetag: Integrating Bottom-up and Top-down Classification in a Social Tagging System", ASIS&T Information Architecture Summit 2007.
【14】 Jakob Voss, "Collaborative thesaurus tagging the Wikipedia way", http://arxiv.org/abs/cs.IR/0604036
【15】 RSS 1.0 Specification, http://web.resource.org/rss/1.0/spec
【16】 FOAF Vocabulary Specification, http://xmlns.com/foaf/0.1/
【17】 Resource Description Framework (RDF), http://www.w3.org/RDF/
【18】 RDF Schema, http://www.w3.org/TR/rdf-schema/
【19】 OWL Web Ontology Language, http://www.w3.org/TR/owl-features/
【20】 Ruby on Rails, http://www.rubyonrails.org/
【21】 IMDb, http://www.imdb.com/
【22】 Jena, http://jena.sourceforge.net/
描述 碩士
國立政治大學
資訊科學學系
94753024
96
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0094753024
資料類型 thesis
dc.contributor.advisor 胡毓忠zh_TW
dc.contributor.advisor Hu, Yuh Jong,en_US
dc.contributor.author (Authors) 宋昆銘zh_TW
dc.creator (作者) 宋昆銘zh_TW
dc.date (日期) 2007en_US
dc.date.accessioned 17-Sep-2009 14:03:14 (UTC+8)-
dc.date.available 17-Sep-2009 14:03:14 (UTC+8)-
dc.date.issued (上傳時間) 17-Sep-2009 14:03:14 (UTC+8)-
dc.identifier (Other Identifiers) G0094753024en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/32683-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊科學學系zh_TW
dc.description (描述) 94753024zh_TW
dc.description (描述) 96zh_TW
dc.description.abstract (摘要) 我們從自然語言領域中借用Thesaurus模型作為字彙關聯的基礎,陸續加入Folksonomy概念、Social Network Service指標的蒐集以及domain-specific ontology來建構Tag-Thesaurus模型,用來解決使用一般tagging system資源彙整能力不足的問題。首先我們對將要實驗的領域選取初始字彙,並利用這些字彙建構Tag-Thesaurus模型。接著將預先準備的這些字彙釋放到社會網路服務平台的tagging system中,透過社會網路服務平台中的tagging system來蒐集使用者對於資源的平面分類資訊,利用這些資訊來對Tag-Thesaurus模型持續地擴充。透過這樣的Tag-Thesaurus模型,我們將可以獲得較佳的資源彙整。domain-specific ontology的加入將可以強化由上而下的資源彙整。而Social Network Service當中的其他資訊,如FOAF[16]或是個人的偏好等,將可以提昇個人化資源彙整的能力。這樣的結合方式不僅是ontology應用的示範,我們更希望透過這樣的混合式模型,使得Web 2.0這樣子廣泛蒐集眾人智慧的概念能夠成為跨入語意網的橋樑。zh_TW
dc.description.abstract (摘要) We aggregate various resources through the Tag-Thesaurus Model. There are three parts in Tag-Thesaurus model, the Folksonomy formal model, indices collection on Social Network Service, and lightweight domain-specific ontology. The Folksnomy model reconstruct relationships between tags, and we can aggregate resources by tags. The indices collection on Social Network Service help us to decide which resource are more important. Finally, the lightweight domain-specific ontology provide the standard interface to describe the relationships between tags.en_US
dc.description.tableofcontents 第1章 研究介紹 9
第1.1節 研究背景 9
第1.2節 研究目的 10
第1.3節 研究議題 10
第1.4節 各章節簡述 11
第2章 相關文獻回顧 12
第2.1節 標籤系統(Tagging System) 12
第2.2節 社會網路服務 15
第2.3節 源料的發佈與彙整 16
第2.3節 階層式分類、平面式分類與混用式分類 18
第3章 研究的方法 21
第3.1節 預先準備的Tag-Thesaurus模型的雛型 21
第3.2節 平面式分類的正規模型 22
第3.3節 將社會網路元素加入Tag-Thesaurus模型 28
第3.4節 FOAF與特定領域本體論 32
第3.5節 透過Tag-Thesaurus模型達成資源彙整 36
第4章 研究架構 41
第5章 實驗平台與相關開發工具 44
第6章 結論與未來可改進的部分 58
zh_TW
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dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0094753024en_US
dc.subject (關鍵詞) 標籤系統zh_TW
dc.subject (關鍵詞) 社會網路服務zh_TW
dc.subject (關鍵詞) 語意網zh_TW
dc.subject (關鍵詞) 資源彙整zh_TW
dc.subject (關鍵詞) tagging systemsen_US
dc.subject (關鍵詞) social network serviceen_US
dc.subject (關鍵詞) semantic weben_US
dc.subject (關鍵詞) resource aggregationen_US
dc.title (題名) 在社會網路上透過Tag-Thesaurus模型達到有效的資源彙整zh_TW
dc.title (題名) Resource Aggregation via Tag-Thesaurus model on Social Weben_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 【1】 Andreas Hotho, Robert J̈aschke, Christoph Schmitz, Gerd Stumme.“Information Retrieval in Folksonomies: Search and Ranking.” The Semantic Web: Research and Applications.zh_TW
dc.relation.reference (參考文獻) 【2】 Alexandre Passant, Jean-David Sta, Philippe Laublet.“Folksonomies, Ontologies and Corporate Blogging.”http:// apassant.net/blog/tag/blogtalkreloaded.zh_TW
dc.relation.reference (參考文獻) 【3】 Andreas Hotho, Robert J¨aschke, Christoph Schmitz,“FolkRank: A Ranking Algorithm for Folksonomies” Proc. FGIR 2006.zh_TW
dc.relation.reference (參考文獻) 【4】 Hongwei Zhu, Michael D. Siegel, Stuart E. Madnick, Pablo Castells.“Information Aggregation – A Value-added E-Service.” Proceedings of the International Conference on Technology, Policy, and Innovation: Critical Infrastructures, The Netherlands, June 26-29, 2001.zh_TW
dc.relation.reference (參考文獻) 【5】 Peter Mika.“Flink: Semantic Web Technology for the Extraction and Analysis of Social Networks.” Journal of Web Semantics(2005).zh_TW
dc.relation.reference (參考文獻) 【6】 Scott A. Golder and Bernardo A. Huberman.“The Structure of Collaborative Tagging Systems.” Arxiv preprint cs.DL/0508082, 2005.zh_TW
dc.relation.reference (參考文獻) 【7】 Thomas Gruber.“Ontology of Folksonomy: A Mash-up of Apples and Oranges.” Invited paper/keynote to the First on-Line conference on Metadata and Semantics Research (MTSR`05).zh_TW
dc.relation.reference (參考文獻) 【8】 Clay Shirky, "Ontology is Overrated: Categories, Links, and Tags", http://www.shirky.com/writings/ontology_overrated.htmlzh_TW
dc.relation.reference (參考文獻) 【9】 Jakob Voss, "Tagging, Folksonomy & Co-Renaissance of Manual Indexing?", Systems of Knowledge Organization for Digital Libraries:Beyond Traditional Authority files. CLIR Publications, 2000.zh_TW
dc.relation.reference (參考文獻) 【10】 Cameron Marlow, "Position Paper, Tagging, Taxonomy, Flickr, Article, ToRead", Hypertext 2006.zh_TW
dc.relation.reference (參考文獻) 【11】 Scott A. Golder, "Usage patterns of collaborative tagging systems", Journal of Information Science.zh_TW
dc.relation.reference (參考文獻) 【12】 Paul Heymann, "Collaborative Creation of Communal Hierarchical Taxonomies in Social Tagging Systems", Berlin EuroIA Summit 2006.zh_TW
dc.relation.reference (參考文獻) 【13】 Emanuele Quintarelli, "Facetag: Integrating Bottom-up and Top-down Classification in a Social Tagging System", ASIS&T Information Architecture Summit 2007.zh_TW
dc.relation.reference (參考文獻) 【14】 Jakob Voss, "Collaborative thesaurus tagging the Wikipedia way", http://arxiv.org/abs/cs.IR/0604036zh_TW
dc.relation.reference (參考文獻) 【15】 RSS 1.0 Specification, http://web.resource.org/rss/1.0/speczh_TW
dc.relation.reference (參考文獻) 【16】 FOAF Vocabulary Specification, http://xmlns.com/foaf/0.1/zh_TW
dc.relation.reference (參考文獻) 【17】 Resource Description Framework (RDF), http://www.w3.org/RDF/zh_TW
dc.relation.reference (參考文獻) 【18】 RDF Schema, http://www.w3.org/TR/rdf-schema/zh_TW
dc.relation.reference (參考文獻) 【19】 OWL Web Ontology Language, http://www.w3.org/TR/owl-features/zh_TW
dc.relation.reference (參考文獻) 【20】 Ruby on Rails, http://www.rubyonrails.org/zh_TW
dc.relation.reference (參考文獻) 【21】 IMDb, http://www.imdb.com/zh_TW
dc.relation.reference (參考文獻) 【22】 Jena, http://jena.sourceforge.net/zh_TW