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運用自我組織圖於多語言階層產生與比對之研究 = A Multilingu...
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國立高雄大學資訊管理學系碩士班
運用自我組織圖於多語言階層產生與比對之研究 = A Multilingual Hierarchy Generation and Mapping Method Based on Self-Organizing Maps
Record Type:
Language materials, printed : monographic
Paralel Title:
A Multilingual Hierarchy Generation and Mapping Method Based on Self-Organizing Maps
Author:
蔡恆慈,
Secondary Intellectual Responsibility:
國立高雄大學
Place of Publication:
[高雄市]
Published:
撰者;
Year of Publication:
2009[民98]
Description:
81面圖、表 : 30公分;
Subject:
多國語言資訊檢索
Subject:
multilingual information retrieval
Online resource:
http://handle.ncl.edu.tw/11296/ndltd/36684968244771547274
Notes:
參考書目:面
Notes:
指導教授:楊新章
Summary:
多國語言的文件隨著網際網路發展而迅速增加,多國語言資訊檢索技術的應用成為一個重要的研究議題。本文描述我們在發現多種語言文件上的知識所發展的一個方法。我們從光華雜誌中收集中文與英文的新聞資料,測試語料庫中各有1,000份中英文對照之文件。在本研究中,採用類神經網路中文件分群的方法,即自我組織圖;將多語言的文件加以群集並產生文件階層,最後透過階層比對之方法來協助我們找尋文件間之關聯。我們使用中、英文雙語平行語料庫來建構實驗以發現文件之間的關連性。本研究實驗顯示我們的方法可以獲取不同語言文件間之關係。 With the increasing amount of multilingual texts in the Internet, multilingual information retrieval has become an import research issue. This paper describes our work on developing a method for discovery of knowledge from multilingual documents. We collected English and Chinese news articles from Taiwan-panorama magazine. Our test corpus includes 1,000 pairs of Chinese-English parallel documents. In this study, we adopt a text clustering approach, which apply a neural network approach, namely the self-organizing maps (SOM), to cluster multilingual documents and reveal the hierarchical structure among them. Finally, we can discover relationships among multilingual documents by mapping multilingual hierarchies. We have conducted experiments to uncover relationships of documents based on Chinese-English bilingual parallel corpora. The experimental results show that our multilingual text mining approach may capture conceptual relationships among documents written in different languages.
運用自我組織圖於多語言階層產生與比對之研究 = A Multilingual Hierarchy Generation and Mapping Method Based on Self-Organizing Maps
蔡, 恆慈
運用自我組織圖於多語言階層產生與比對之研究
= A Multilingual Hierarchy Generation and Mapping Method Based on Self-Organizing Maps / 蔡恆慈撰 - [高雄市] : 撰者, 2009[民98]. - 81面 ; 圖、表 ; 30公分.
參考書目:面指導教授:楊新章.
多國語言資訊檢索multilingual information retrieval
運用自我組織圖於多語言階層產生與比對之研究 = A Multilingual Hierarchy Generation and Mapping Method Based on Self-Organizing Maps
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多國語言的文件隨著網際網路發展而迅速增加,多國語言資訊檢索技術的應用成為一個重要的研究議題。本文描述我們在發現多種語言文件上的知識所發展的一個方法。我們從光華雜誌中收集中文與英文的新聞資料,測試語料庫中各有1,000份中英文對照之文件。在本研究中,採用類神經網路中文件分群的方法,即自我組織圖;將多語言的文件加以群集並產生文件階層,最後透過階層比對之方法來協助我們找尋文件間之關聯。我們使用中、英文雙語平行語料庫來建構實驗以發現文件之間的關連性。本研究實驗顯示我們的方法可以獲取不同語言文件間之關係。 With the increasing amount of multilingual texts in the Internet, multilingual information retrieval has become an import research issue. This paper describes our work on developing a method for discovery of knowledge from multilingual documents. We collected English and Chinese news articles from Taiwan-panorama magazine. Our test corpus includes 1,000 pairs of Chinese-English parallel documents. In this study, we adopt a text clustering approach, which apply a neural network approach, namely the self-organizing maps (SOM), to cluster multilingual documents and reveal the hierarchical structure among them. Finally, we can discover relationships among multilingual documents by mapping multilingual hierarchies. We have conducted experiments to uncover relationships of documents based on Chinese-English bilingual parallel corpora. The experimental results show that our multilingual text mining approach may capture conceptual relationships among documents written in different languages.
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