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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 簡立峰(Lee-Feng Chien) | |
dc.contributor.author | Tzu-hsien Yu | en |
dc.contributor.author | 游子賢 | zh_TW |
dc.date.accessioned | 2021-06-13T04:26:37Z | - |
dc.date.available | 2006-07-28 | |
dc.date.copyright | 2006-07-28 | |
dc.date.issued | 2006 | |
dc.date.submitted | 2006-07-21 | |
dc.identifier.citation | J.I. Alvarez-Hamelin, L. Dall’Asta, A. Barrat, and A. Vespignani. k-core decomposition: a tool for the visualization of large scale networks. Arxiv preprint cs.NI/0504107, 2005.
V. Batagelj and A. Mrvar. Pajek – program for large network analysis. Connections, 21(2):47–57, 1998. V. Batagelj and M. Zaversnik. Generalized cores. Arxiv preprint cs.DS/0202039, 2002. V. Batagelj and M. Zaversnik. An o(m) algorithm for cores decomposition of networks. Arxiv preprint cs.DS/0310049, 2003. G. Begelman, P. Keller, and F. Smadja. Automated tag clustering: Improving search and exploration in the tag space. In Collaborative Web Tagging Workshop, 15th International World Wide Web Conference, May 2006. Shui-Lung Chuang and Lee-Feng Chien. Taxonomy generation for text segments: A practical web-based approach. ACM Transactions on Information Systems, 23(4):363–396, October 2005. URL http://dx.doi.org/10.1145/1095872.1095873. Scott Golder and Bernardo A. Huberman. Usage patterns of collaborative tagging systems. Journal of Information Science, 32(2), pages 198–208, April 2006. URL http://dx.doi.org/10.1177/0165551506062337. Paul Heymann and Hector Garcia-Molina. Collaborative creation of communal hierarchical taxonomies in social tagging systems. Technical Report 2006-10, Stanford University, April 2006. URL http://heymann.stanford.edu/taghierarchy.html. Bjornar Larsen and Chinatsu Aone. Fast and effective text mining using linear-time document clustering. In Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 16–22, 1999. Cameron Marlow, Mor Naaman, Danah Boyd, and Marc Davis. Position paper, tagging, taxonomy, flickr, article, toread. In Collaborative Web Tagging Workshop, 15th International World Wide Web Conference, May 2006. Thomas Vander Wal. You down with folksonomy? http://www.vanderwal.net/random/entrysel.php?blog=1529, 2004. J.R. Wen, J.Y. Nie, and H.J. Zhang. Query clustering using user logs. ACM Transactions on Information Systems, 20(1):59–81, 2002. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/33142 | - |
dc.description.abstract | 網際網路上的資訊量成長得相當快,藉由網路上社群的力量,資訊的分類能由大眾來做決定,也就是所謂的通俗分類 (folksonomy),而這些通俗分類中的標籤仍然可以有進一步的組織。本論文中使用了兩種方法將 del.icio.us (一個協同標記系統的網站,能讓使用者儲存並註記自己的網路書籤)中,由搜尋所產生的結果中的共通標籤加以重新整理、分群。
我們將自動產生的分群結果與熟悉相關主題使用者手動分群的結果相比,可得知這兩種自動產生的方法與使用者產生結果的相似度相距不遠,而不同使用者產生的群聚結果也大不相同。我們亦施行了理解度測試,以了解使用者是否能從產生的群聚結果中獲得助益。我們認為,組織分群後的標籤的確能讓使用者更快熟悉其搜尋的概念,以及幫助其導覽。 | zh_TW |
dc.description.abstract | Information grows fast in volume on the Internet. By the power of the Web communities, clasffication of information is done by the public -- the 'folksonomy'. However, we still want to further utilize those collaborative generated tags in the folksonomy system. In this thesis, we survey two approaches to organizing and clustering the common tags of the search results from a collaborative tagging system 'del.icio.us' which let users store and annotate their bookmarks.
We compare the automatically generated clustering results with those by humans who are familiar with the topics. We observe that the results of the two approaches we survey have close similarities with those by the people. And even people can not agree on the clustering. We then conduct a comprehension test to see if people really benefit from the results. We believe that the organized tags really help users in framing their concepts and navigation. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T04:26:37Z (GMT). No. of bitstreams: 1 ntu-95-R93725006-1.pdf: 605657 bytes, checksum: 82d1f757e0164d326fb82d48364a3f5f (MD5) Previous issue date: 2006 | en |
dc.description.tableofcontents | 謝詞 - iii
中文摘要 - iv Abstract - v Table of Contents - vi List of Tables - ix List of Figures - x 1 Introduction - 1 1.1 Research motivations - 1 1.2 The considered problems - 3 1.3 Approaches and results - 4 1.4 Organization of this thesis - 4 2 Related works - 5 2.1 Introduction to tagging and folksonomies - 5 2.1.1 Tagging - 5 2.1.2 Folksonomies - 6 2.1.3 Advantages and disadvantages of folksonomies - 6 2.1.4 Related works on folksonomies - 8 2.2 Clustering - 8 2.2.1 Term clustering - 8 2.2.2 Clustering tags - 9 3 Web-based clustering approach - 11 3.1 Details of this approach - 11 3.2 Procedure for experiments - 12 3.3 Constructing a test query set - 13 3.4 Experiment results - 13 3.5 Discussion - 14 3.5.1 Applicability of this approach on clustering tags - 14 3.5.2 Drawbacks of this approach - 14 3.6 The online system - 15 4 Graphical approach - 16 4.1 k-core - 16 4.2 Procedure for experiments - 17 4.3 Experiment results - 18 4.4 Discussion - 20 4.4.1 Drawbacks of this approach - 21 4.4.2 Why it doesn't work in some cases - 21 5 Evaluation and user studies - 23 5.1 F-measure - 23 5.2 Comparing with human-constructed results - 24 5.2.1 The method - 24 5.2.2 Problems of the evaluation - 25 5.2.3 Results - 25 5.2.4 Discussion - 25 5.3 Comparisons among human results - 27 5.4 Comprehension test - 29 6 Conclusion and future work - 31 6.1 Conclusion - 31 6.2 Future work - 32 Bibliography - 33 | |
dc.language.iso | en | |
dc.title | 通俗分類標記之自動組織 | zh_TW |
dc.title | Automatic organization of user-generated tags from the Web | en |
dc.type | Thesis | |
dc.date.schoolyear | 94-2 | |
dc.description.degree | 碩士 | |
dc.contributor.coadvisor | 王柏堯(Bow-Yaw Wang) | |
dc.contributor.oralexamcommittee | 莊裕澤(Yuh-Jzer Joung),卜小蝶(Hsiao-Tieh Pu),張嘉惠(Chia-Hui Chang) | |
dc.subject.keyword | 標記,協同標記,通俗分類,del.icio.us,全球資訊網,分群, | zh_TW |
dc.subject.keyword | tagging,collaborative tagging,folksonomy,del.icio.us,Web,clustering, | en |
dc.relation.page | 34 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2006-07-22 | |
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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