請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/9512完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 許永真 | |
| dc.contributor.author | Yi-Ching Huang | en |
| dc.contributor.author | 黃怡靜 | zh_TW |
| dc.date.accessioned | 2021-05-20T20:26:12Z | - |
| dc.date.available | 2008-09-02 | |
| dc.date.available | 2021-05-20T20:26:12Z | - |
| dc.date.copyright | 2008-09-02 | |
| dc.date.issued | 2008 | |
| dc.date.submitted | 2008-08-26 | |
| dc.identifier.citation | [1] M. Ames and M. Naaman. Why we tag: motivations for annotation in mobile and online media. In CHI '07: Proceedings of the SIGCHI conference on Human factors in computing systems, pages 971--980, New York, NY, USA, 2007. ACM Press.
[2] E. Bertino, G. P. Zarri, and B. Catania. Intelligent Database Systems. Addison-Wesley Professional, 2001. [3] A. Collins and E. Loftus. A spreading-activation theory of semantic processing. Psychological Review, 82:407--428, 1975. [4] C. Fellbaum. Wordnet: An Electronic Lexical Database. MIT Press, March 1998. [5] S. A. Golder and B. A. Huberman. The structure of collaborative tagging systems, Aug 2005. [6] S. A. Golder and B. A. Huberman. Usage patterns of collaborative tagging systems. Journal of Information Science, 32(2):198--208, April 2006. [7] Y. Hasan-Montero and V. Herrero-Solana. Improving tag-clouds as a visual information retrieval interfaces. In Proceedings of International Conference on Multidisciplinary Information Sciences and Technologies, October 2006. [8] Y.-C. Huang, C.-C. Hung, and J. Y.-j. Hsu. You are what you tag. In Proceedings of AAAI 2008 Spring Symposium Series on Social Information Processing, Stanford University, California, March 2008. [9] B. Kerr. Tagorbitals: a tag index visualization. In SIGGRAPH '06: ACM SIGGRAPH 2006 Sketches, New York, NY, USA, 2006. ACM. [10] H. Liu and P. Maes. InterestMap: Harvesting social network profiles for recommendations. In Proceedings of the Beyond Personalization 2005 Workshop, 2005. [11] H. Liu and P. Singh. Conceptnet: A practical commonsense reasoning toolkit. BT Technology Journal, 22, 2004. [12] C. Marlow, M. Naaman, D. Boyd, and M. Davis. Ht06, tagging paper, taxonomy, flickr, academic article, to read. In HYPERTEXT '06: Proceedings of the seventeenth conference on Hypertext and hypermedia, pages 31--40, New York, NY, USA, 2006. ACM. [13] A. Mathes. Folksonomies - cooperative classification and communication through shared metadata, December 2004. [14] E. Michlmayr and S. Cayzer. Learning user profiles from tagging data and leveraging them for personal(ized) information access. In Proceedings of the Workshop on Tagging and Metadata for Social Information Organization, 16th International World Wide Web Conference (WWW2007), May 2007. [15] G. A. Miller, R. Beckwith, C. Fellbaum, D. Gross, and K. J. Miller. Introduction to wordnet: An on-line lexical database*. in International Journal of Lexicography, 3(4): 235--244, January 1990. [16] T. Pedersen, S. V. Pakhomov, S. Patwardhan, and C. G. Chute. Measures of semantic similarity and relatedness in the biomedical domain. Journal of Biomedical Informatics, 40(3):288--299, June 2007. [17] T. Pedersen, S. Patwardhan, and J. Michelizzi. Wordnet::similarity - measuring the relatedness of concepts. In Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (AAAI-08), pages 1024--1025, San Jose, CA, July 25-29 2004. [18] R. Sinha. A social analysis of tagging. World Wide Web electronic publication, 2006. [19] M. Stefaner. Visual tools for the socio--semantic web. Master's thesis, University of Applied Sciences Potsdam, June 2007. [20] J. Voss. Tagging, folksonomy & co-renaissance of manual indexing? Arxiv preprint cs/0701072, 2007. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/9512 | - |
| dc.description.abstract | 人們使用個人化的使用者描述（personal profile）來呈現自己的興趣與特色，並且取得許多線上的服務。這些使用者描述通常不夠完整，它們只包含了簡單的基本描述，而且只能主觀的呈現使用者自己的想法，無法反映出使用者興趣的動態變化，所以它們無法充分顯現個人的特質。在這篇論文裡，我們提出了附有語意關係的標籤式使用者描述的概念與方法。在概念上，意指我們可以利用所擁有的社群多媒體資料中所附含的標籤，有效的建立符合個人興趣與特質的使用者描述。在方法上，我們使用附有權重的標籤與不同強度的語意關係，來顯現使用者的想法與興趣。常識運算（common sense computing）與共現頻率（co-occurrence）能夠用來計算出不同標籤之間的語意關係。為了突顯出使用者標籤描述的特色與不同面向之間的差異，我們將使用者描述以標籤雲的方式做視覺化的呈現，並且加入了三維度的轉場效果，讓使用者更直覺、更自然的利用這樣的介面去搜尋在社群網路上的資料。 | zh_TW |
| dc.description.abstract | People construct personal profiles for self presentation and for obtaining online services. Profiles consisting of simple factual data provide an inadequate description of the individual, as they are often incomplete, mostly subjective and cannot reflect dynamic changes. This thesis explores the idea of ``you-are-what-you-tag', namely, an individual can be effectively profiled by the tags associated with his/her social media. Specifically, this thesis proposes semantic tag-based profiles, profiles that can be represented as a set of semantically related and weighted tags. The strength of the semantic relationships between these tags are calculated using common sense computing and co-occurrence measurements. Moreover, different views of these profiles are visualized as tag clouds via a 3D switch effect. The proposed approach supports an intuitive and novel interface for people to browse/search through a social web site. | en |
| dc.description.provenance | Made available in DSpace on 2021-05-20T20:26:12Z (GMT). No. of bitstreams: 1 ntu-97-R95922045-1.pdf: 3810690 bytes, checksum: b8c9cd9a48990f9deb509b2904e1d6c0 (MD5) Previous issue date: 2008 | en |
| dc.description.tableofcontents | Acknowledgments i
Abstract iii List of Figures ix List of Tables xi Chapter 1 Introduction 1 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Research Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.4 Thesis Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Chapter 2 RelatedWork 5 2.1 Tagging and Folksonomy . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Design of Tagging Systems . . . . . . . . . . . . . . . . . . . . . . . 6 2.3 Common Sense Computing . . . . . . . . . . . . . . . . . . . . . . . 8 2.3.1 Cyc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.3.2 WordNet . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.3.3 Open Mind Common Sense . . . . . . . . . . . . . . . . . . 10 2.3.4 ConceptNet . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.3.5 Semantic Similarity Analysis . . . . . . . . . . . . . . . . . . 10 2.4 User Profiling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.5 Tag-based and Social Visualization . . . . . . . . . . . . . . . . . . . 14 2.5.1 Typical Tag Visualization . . . . . . . . . . . . . . . . . . . . 15 2.5.2 Tag Orbital . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Chapter 3 Tag-based Profile with Semantic Relationship 19 3.1 Problem Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 3.2 Proposed Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.2.1 Semantic Tag-based Profile . . . . . . . . . . . . . . . . . . 21 3.2.2 Tag-based Profile Presentation . . . . . . . . . . . . . . . . . 22 Chapter 4 Semantic Relationship Analysis 23 4.1 Three Types of Knowledge . . . . . . . . . . . . . . . . . . . . . . . 24 4.2 Personal Association: Co-occurrence . . . . . . . . . . . . . . . . . . 25 4.3 Community Knowledge: Social Wisdom . . . . . . . . . . . . . . . . 27 4.4 Global Knowledge: Semantic Similarity . . . . . . . . . . . . . . . . 28 4.4.1 WordNet-based similarity . . . . . . . . . . . . . . . . . . . 28 4.4.2 ConceptNet-based similarity . . . . . . . . . . . . . . . . . . 29 4.5 Semantic-based Co-occurrence . . . . . . . . . . . . . . . . . . . . . 32 4.5.1 Tag Concept Based on Semantic Similarity . . . . . . . . . . 33 4.5.2 Semantic Co-occurrence Based on Tag Concept . . . . . . . . 34 Chapter 5 Tag-based Profile Presentation 36 5.1 Data Characteristic . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 5.2 Our Idea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 5.3 Profile Presentation From Three Viewpoints . . . . . . . . . . . . . . 39 Chapter 6 Experiment and Evaluation 42 6.1 Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 6.2 User Study Design . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 6.3 Experiment Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Chapter 7 Conclusion 49 7.1 Summary of Contributions . . . . . . . . . . . . . . . . . . . . . . . 50 7.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 Bibliography 52 | |
| dc.language.iso | en | |
| dc.title | 賦有語意關聯的視覺化標籤式使用者描述 | zh_TW |
| dc.title | Tag-based Profile Presentation with Semantic Relationship | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 96-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 吳家麟,陳穎平,林守德,歐昱言 | |
| dc.subject.keyword | 標註,使用者描述,社群媒體,語意分析,語意關聯,視覺化呈現, | zh_TW |
| dc.subject.keyword | tagging,user profiling,social media,semantic analysis,semantic relationship,presentation, | en |
| dc.relation.page | 53 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2008-08-27 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-97-1.pdf | 3.72 MB | Adobe PDF | 檢視/開啟 |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。