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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 簡立峰(Lee-Feng Chien) | |
dc.contributor.author | Jay Stu | en |
dc.contributor.author | 司徒傑 | zh_TW |
dc.date.accessioned | 2021-06-13T04:25:29Z | - |
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 | References
[1] Staurt E. Middleton and David C. de Roure. Ontological User Profiling in Recommender Systems. In ACM Tansaction on Information Systems 2004 [2] Kazunari Sugiyama. Adaptive Web Search Based on User Profiles Constructed without Any Effort from users. In www2004 [3] http://www.google.com [4] http://www.yahoo.com[5] Jason Chaffee and Susan Gauch. Personal Ontologie for Web Navigation. In CIKM 2000. [6] http://www.amazon.com [7] Badrul M. Sarwar, Application of Dimensionality Reduction in Recommender System -- A Case Study. In ACM WebKDD 2000 Web Mining for E-Commerce Workshop, 2000 [8] Harry Bruce, William Jones and Susan Dumais. Information behavior that keeps found things found. In Information Research, Vol. 10 No. 1, October 2004 [9] Liberman, H. Letizia: An Agent that Assists Web Browsing. IJCAI-95, pp. 924-929. [10] Mladenic, D. Personal WebWatcher: Implementation and Design, Technical Report IJS-DP-7472, Department for Intelligent Systems, J.Stefan Institute, October, 1996. [11] Gediminas Adomavicius. User Profiling in Personalization Applications through Rule Discovery and Validation. In KDD 99 [12] http://www.cordis.lu/ist/ka1/administrations/publications/glossary.htm [13] J Teevan, ST Dumais, E Horvitz. Personalizing search via automated analysis of interests and activities. In Proceedings of SIGIR, 2005. [14] Google suggest. http://www.google.com/webhp?hl=en&complete=1 [15] Mladenic, D., (2001). Using Text Learning to help Web browsing. In Proceedings of the 9th International Conference on Human-Computer Interaction [18] Jacob Nielson. The art of navigating through hypertext. In Communications of the ACM Volume 33 , Issue 3 (March 1990) Pages: 296 - 310 [19] Is Navigation useful? http://www.useit.com/alertbox/20000109.html [20] Ellem Spertus. ParaSite: Mining Structural Information on the Web In Computer Networks and ISDN Systems Volume 29 ,Issue 8-13 (September 1997) Pages: 1205 – 1215 [21] Liberman, H. Letizia: An Agent that Assits Web Browsing. In IJCAI-95, pp. 924-929 [22] D Goldberg, D Nichols, BM Oki, D Terry Using collaborative filtering to weave an information tapestry In Communications of the ACM, 1992 [23] http://www.anvilmediainc.com/search-engine-marketing-glossary.html [24] Taxonomies are what? http://www.freepint.com/issues/041001.htm#feature [25] Y Labrou, T Finin Yahoo! As an Ontology: Using Yahoo! Categories to Describe Documents - CIKM, 1999 [26] Personalized web search by mapping user queries to categories F Liu, CT Yu, W Meng - CIKM, 2002 - portal.acm.org [27] Deborah L. McGuinness. 'Ontologies Come of Age'. In Dieter Fensel, J im Hendler, Henry Lieberman, and Wolfgang Wahlster, editors. Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential. MIT Press, 2002. [28] Gerard Salton and Christopher Buckley. Term-weighting approaches in automatic text retrieval. In Information Processing and Management: an International Journal Volume 24, Issue 5 1988 Pages: 513 - 523 [29] Chien L.-F.PAT-tree-based adaptive keyphrase extraction for intelligent Chinese information retrieval In Information Processing and Management, Volume 35,Number 4, July 1999, pp. 501-521(21) [30] A Comprehensive Comparative Study on Term Weighting Schemes for Text Categorization with Support Vector Machines [31] Shen, X. and Zhai, C. X. (2003). Exploiting query history for document ranking in interactive information retrieval. In Proceedings of SIGIR‘03 (Poster), 377-378. [32] Speretta, M. and Gauch, S. (2004). Personalizing search based on user search history. Submitted to CIKM ‘04. http://www.ittc.ku.edu/keyconcept/ [33] Google personalized search http://www.google.com/searchhistory/ [34] Jeh, G. and Widom, J. (2003). Scaling personalized Web search. In Proceedings of WWW ‘03, 271-279. [35] Morita, M. and Shinoda, Y. (1994). Information filtering based on user behavior analysis and best match text retrieval.In Proceedings of SIGIR ‘94, 272-281 [36] Kritikopoulos, A. and Sideri, M. (2003). The Compass Filter: Search engine result personalization using Web communities. In Proceedings of ITWP. [37] Eurekster swicki http://swicki.eurekster.com/ [38] Shui-Lung Chuang, Lee-Feng Chien: Enriching Web taxonomies through subject categorization of query terms from search engine logs. Decision Support Systems 35(1): 113-127 (2003) [39] Hsiao-Tieh Pu, Shui-Lung Chuang, Chyan Yang: Subject categorization of query terms for exploring Web users' search interests. JASIST 53(8): 617-630 (2002) | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/33113 | - |
dc.description.abstract | 個人化的應用在網路世代一直是一個相當重要的研究方向,透過個人化的服務能更貼近使用者的需求,本研究旨在運用術語分類的技術從網路客戶端的資料來源中探求使用者在獲取資訊時所擁有的偏好或興趣,要決定使用者有哪些特殊偏好,我們首先從客戶端(例如個人電腦)中的大量儲存的歷史文件資料作抽詞的動作,本研究著重於三項資料來源:使用者搜尋關鍵詞、瀏覽過的網頁及電子郵件,之後我們將整理出來的關鍵術語再透過術語分類的技術來決定術語的分類目錄,以建立使用者各個不同百分比的目錄分布,本研究對五個志願使用者作實驗,從各個不同資料來源來產生目錄分布,並且對產生出的目錄分布做簡單的觀察分析。
這項簡單的方法並未涉及太深的分析與架構,在各階段的轉換還有很多的討論空間,例如個人目錄的分布轉換到個人偏好的探討,但我們相信這是一個有潛力的方法去實踐各種不同的個人化應用,例如個人化搜尋、個人資訊過濾與推薦系統。 | zh_TW |
dc.description.abstract | This thesis is developed for discovering the personal preferences from different data sources that stored in web client side like personal computers. To determine the personal preferences, we first extract key terms from different data sources to be the material of the next step, there are three major data sources:search keywords, browsed pages and e-mails. And then we use term categorization method on the key terms to generate user profiles that contains the distributions of different categories. After the simple method, we do some observations of five users to discuss the appearance of the personal categories.
This method is really simple and has more space to discuss about the transformation between term categories and personal preferences. We hope the simple method can be a potential way to perform personalization applications, like personalized search, personal information filtering or recommendation system. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T04:25:29Z (GMT). No. of bitstreams: 1 ntu-95-R93725045-1.pdf: 1483822 bytes, checksum: 2772556e255b26f925d5b731a99735d9 (MD5) Previous issue date: 2006 | en |
dc.description.tableofcontents | Table of content
Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Research goal 1 1.3 Thesis organization 2 1.4 Possible applications 3 Chapter 2 Related Work 4 2.1 Personalization Systems 4 2.2 User behaviors 6 2.3 User profiling and personalized search 9 2.4 Term extraction 12 2.5 Knowledge architecture 13 Chapter 3: The Approach 17 3.1. Term extraction 17 3.2 Term categorization 19 Chapter 4 Evaluation 24 4.1 Experiment settings 24 4.2 Categorization performance 24 4.3 Categorization accuracy on user profiles n 27 4.4 User study 30 5.1 Observations and problems 33 5.2 Possible Applications 34 5.3 Conclusions 36 References 37 | |
dc.language.iso | en | |
dc.title | 以術語分類從網路客戶端探求個人化偏好 | zh_TW |
dc.title | A Term Categorization Approach to Discovery of Personal Preferences from Web Clients | en |
dc.type | Thesis | |
dc.date.schoolyear | 94-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 王柏堯,陳信希,陳宜欣,蔡益坤 | |
dc.subject.keyword | 個人化,使用者歸檔化,術語分類,使用者分析, | zh_TW |
dc.subject.keyword | Personalization,User profiling,Term categorization,User analysis, | en |
dc.relation.page | 39 | |
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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