博碩士論文 954203043 詳細資訊




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姓名 吳政穎(Jheng-ying Wu)  查詢紙本館藏   畢業系所 資訊管理學系
論文名稱 利用相關回饋建立概念化的使用者興趣檔以協助使用者進行網頁查詢
(Applying Relevance Feedback in the Construction of Conceptual User Profile for Webpage Retrieval)
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摘要(中) 在網路搜尋上,對於不同背景與需求的使用者,一個相同的查詢句,所得到的搜尋結果卻都是相同的大量網頁,這使得個人化搜尋的需求越來越高。使用者興趣檔描述了一個特定使用者的興趣,通常用來幫助搜尋引擎提供個人化的搜尋結果或者應用在推薦系統上。在過去的研究中,使用者興趣檔大部分是依照使用者的瀏覽歷史所建立而成的,而此種使用者興趣檔所代表的資訊,主要為使用者長期的資訊需求,而非單次檢索的資訊需求。
本研究提出了一套方法,藉由相關回饋來擷取出使用者的查詢概念,並應用概念擷取的技術來建立概念化的使用者興趣檔,以此改善反映使用者長期性資訊需求的興趣檔在單次資訊檢索中可能檢索出與使用者資訊需求不符的情況,並希冀能協助使用者從大量的搜尋結果中找出與其資訊需求相關的網頁。
摘要(英) In web search, users usually get the same results for the same query, even if they have different interests and backgrounds. It makes the increase of the demand for personalized search increase. A user profile is the description of a specific user interest. It has been used by search engines to provide personalized search results or applied in recommending system. In the past, personalized search usually relies on searching history for personal interest extraction.
In this research we have tried to apply relevance feedback to extract user’s information needs, and apply the technology of concept extraction in the construction of conceptual user profile. It aims to help users to find out the related webpages in numerous search results.
關鍵字(中) ★ 個人化搜尋
★ 使用者興趣檔
★ 資訊需求
★ 概念擷取
關鍵字(英) ★ personalized search
★ user profile
★ information needs
★ concept extraction
論文目次 一、緒論 1
1-1研究背景與動機 1
1-2研究目的 2
1-3研究範圍與限制 2
1-4研究流程 3
1-5論文架構 3
二、文獻探討 5
2-1概念(CONCEPT)相關研究 5
2-2字詞權重(TERM WEIGHTING)相關研究 9
三、系統設計 12
3-1系統流程 12
3-2系統架構 19
四、實驗分析 21
4-1實驗設計與流程 21
4-2實驗結果與分析 22
五、結論 31
參考文獻 33
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[2] D. K. Limbu, A. Connor, R. Pears & S. MacDonell, “Contextual relevance feedback in web information retrieval,” Proceedings of the 1st international conference on Information interaction in context, Copenhagen, Denmark, pp. 138-143, 2006.
[3] F. Liu, C. Yu & W. Meng, “Personalized Web Search by Mapping User Queries to Categories,” Proceedings of the eleventh international conference on Information and knowledge management, McLean, Virginia, USA , pp. 558-565, 2002.
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[15] R. Lecceuche, “Finding Comparatively Important Concepts between Texts,” Proceedings of the 15th IEEE international conference on Automated software engineering, Washington, DC, USA, pp.55, 2000.
[16] V. Fresno & A. Ribeiro, “An Analystical Approach to Concept Extraction in HTML Environments,” Journal of Intelligent Information Systems, 22(3), pp. 215-235, 2004.
[17] V. Fresno, R. Martinez & S. Montalvo, “Improving Web Page Clustering Through Selecting Appropriate Term Weighting Functions,” Proceedings of the Web Mining Workshop into the IEEE 1st International Conference on Digital Information Management, Bangalore, India, pp. 511-518, 2006.
[18] Y. Chang, M. Kim & V. V. Raghavan, “Construction of Query Concepts Based on Feature Clustering of Documents,” Information Retrieval, 9(3), pp. 231-248, 2006.
[19] Z. N. Zacharis & T. Panayiotopoulos, “Web Search Using a Genetic Algorith,” IEEE Internet Computing, 5(2), pp. 18-26, 2001.
[20] D. Sullivan, “The order you are, the more you want personalized search,” 2004, http://searchenginewatch.com/searchday/article.php/3385131
指導教授 周世傑(Shih-chieh Chou) 審核日期 2008-7-14
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