鄭卜壬Cheng, Pu-Jen臺灣大學:資訊網路與多媒體研究所林信仲Lin, Hsin-ChungHsin-ChungLin2010-05-052018-07-052010-05-052018-07-052008U0001-2107200811295500http://ntur.lib.ntu.edu.tw//handle/246246/180600在本篇論文中，我們定義了以概念為基礎之實體相似度搜尋這個問題。在實體相似度搜尋中，我們輸入一個查詢詞以及所要搜尋的實體類型，這個搜尋系統會回覆一個經過排序後的列表，列表上有經過排序後的實體，其實體的形態為使用者輸入要查詢的型態。此列表排序的依據為跟查詢詞的相似度。在實體相似度搜尋中如何排序是一個關鍵的議題。在之前的文獻中，抽取實體的文獻是專注於如何抽取正確的實體，而實體排序的文獻則是專注於如何依據實體間的關切程度來排序實體。一般而言，還有許多其他的特徵可以用在排序實體相似度搜尋，而不是只有取決於上下文的特徵。我們提出一個可用在網上相似度搜尋的普遍架構。這個架構可以依據使用者的回饋來自動調整計算相似度的函式。我們對這個問題有一個假設就是在概念上實體之間會有語意上的關係。我們驗證我們的線上原型系統使用線上的搜集到的資料，而且證明我們的方法是能運作成功的。In this paper we address the problem of concept-based entity similarity search. In entity similarity search, given a query and an entity type, a search system returns a ranked list of entities in the type (e.g., person name, e-mail) relevant to the query. Ranking is a key issue in entity similarity search. In literature, entity extraction focuses on how to extract correct entities and entity ranking focuses on the ranking of entities according to the relevance between entities. In general, many features may be useful for ranking in entity similarity search no more than the contextual feature. We propose a general framework for entity similarity search on the web. And this framework is able to adjust the similarity function according to the user’s relevance feedback. The assumption of this problem, we propose there are semantic relationships among entities at conceptual level. We evaluate our online prototype over a Web corpus, and show that our approach performs effectively.摘要........................................................................................................................................... iiBSTRACT .............................................................................................................................. iiicknowledgements...................................................................................................................ivist of Figures ..........................................................................................................................viiist of Tables.......................................................................................................................... viiihapter 1: Introduction.............................................................................................................1.1 Motivation........................................................................................................................1.2 Previous Work..................................................................................................................3.3 Basic Idea..........................................................................................................................3.4 Challenges........................................................................................................................4.6 Experiments.....................................................................................................................4.7 Contributions...................................................................................................................4hapter 2: Related Work...........................................................................................................5.1 Entity Extraction .......................................................................................................5.2 Entity Ranking...........................................................................................................7.3 Conceptual Space Model............................................................................................8hapter 3: The Problem ............................................................................................................9hapter 4: Our Approach....................................................................................................... 13.1 Overview................................................................................................................. 14.2 Entity Extraction .................................................................................................... 14.3 Feature Extraction.................................................................................................. 18.3.1 Weight of the Entity-Type Features ....................................................................... 18.3.2 Extract Taxonomy-Type Features.......................................................................... 20.3.3 Extract Web-Type Features................................................................................... 25.4 Learning Similarity Function ................................................................................. 32.4.1 Similarity measure functions mijk........................................................................... 35.4.2 Update of ij W ...................................................................................................... 35.4.3 Update of ijk W ..................................................................................................... 37hapter 5: Experiments .......................................................................................................... 39.1 Overview ................................................................................................................. 39.2 Data Set ................................................................................................................... 39.3 Entity Search ............................................................................................................ 39.4 Relevance Feedback ................................................................................................. 42hapter 6: Discussion ............................................................................................................. 46hapter 7: Applications .......................................................................................................... 48.1 Recommender System .............................................................................................. 48.2 Cluster ..................................................................................................................... 49hapter 8: Conclusion and Future work ................................................................................ 50eferences ............................................................................................................................... 51application/pdf1277594 bytesapplication/pdfen-US實體搜尋實體相似度Entity SearchEntity Similaritythesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/180600/1/ntu-97-R95944027-1.pdf