使用查詢擴展技術及支援向量機由網路資料集挖掘中文姓名翻譯

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研究生：	陳威達 Wei-Da Chen
論文名稱：	使用查詢擴展技術及支援向量機由網路資料集挖掘中文姓名翻譯 Mining Translations of Chinese Names from Web Corpora by Using a Query Expansion Technique and Support Vector Machine
指導教授：	李漢銘 Hahn-Ming Lee 何建明 Jan-Ming Ho
口試委員:	王勝德 Sheng-De Wang 李育杰 Yuh-Jye Lee 王榮英 Jung-Ying Wang
學位類別：	碩士 Master
系所名稱：	電資學院 - 資訊工程系 Department of Computer Science and Information Engineering
論文出版年：	2007
畢業學年度：	95
語文別：	英文
論文頁數：	78
中文關鍵詞：	資料探勘、姓名翻譯、查詢擴展、支援向量機
外文關鍵詞：	Data mining, Name translation, Query expansion, Suppot Vector Machine
相關次數：	點閱：309 下載：1
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中文姓名翻譯是屬於專名實體翻譯中的一種特殊案例。因為在翻譯中文姓名的方法中存在許多不同種類的羅馬拼音系統，且許多人會在所翻譯過的名字中添加額外與本身中文姓名不相關的字。而將某學者的姓名正確的翻譯成英文將能夠對人們在網路上尋找此學者的相關學術成就有很大的幫助，因此中文姓名的翻譯成為一個重要的議題。
在這篇論文中,我們首先提出一個為中文姓名之翻譯分類的方法,接著提出一個新的方法來從網路資料集中挖掘出中文姓名的翻譯。我們的方法利用查詢擴展技術及支援向量機與“發音”與“距離”這兩種特徵來設法取得可能的姓名翻譯。利用查詢擴展技術能夠有效且更精確的回收同時含有輸入人名與其英文翻譯的網頁，而利用支援向量機透過範例的訓練學習來判別姓名翻譯候選的正確與否可減少使用啟發式法則時因主觀判斷而產生的副作用。我們將中文姓名依其相對應的英文翻譯分成八種類型，實驗結果顯示我們的方法可將三種較常見的類型有效的翻譯。

Chinese name translation is a special case of the problem of named entity translation. It is a very challenging problem because there exist many kinds of Romanization systems and some people like to add some words to their English names. Because of translating a scholar’s name into its corresponding English name correctly could help find information about his academic achievements, Chinese name translation is in great demand.
In this thesis, we first propose a classification of Chinese names, and then propose a novel methodology to mining Chinese name translations from Web corpora. Our methodology uses two kinds of features, which are the phonetic and the distant features, to extract name translation candidates by using a query expansion technique and Support Vector Machine (SVM). Using query expansion technique can effectively and more precisely retrieve the Web pages which contained the input Chinese name and the name’s translation. And using SVM to learn verification rule by training samples for name translation candidates can avoid the side effect caused by using heuristic rule. We classify Chinese names into eight name types according to the corresponding name translation. The experiment result showed our methodology can effectively mine out the correct name translations of three common name types.

Content
Abstract	II
Acknowledgements	IV
Content	V
List of Tables	VI
List of Figures	VII
Chpater 1	Introduction	1
Chpater 2	Background	10
Chpater 3	Chinese Name Translation Mining System (CNTMS)	19
Chpater 4	Experiments	33
Chpater 5	Discussion and Conclusion	47
References	55
Vita	65

List of Tables
Table 1. 8 Types of translated Chinese name formats	3
Table 2. Distribution of Database I & Database II	36

List of Figures
Figure 1. Returned Web page snippets by using a person’s name and surname translation as a query	6
Figure 2. A common example of translating movie title in Chinese	13
Figure 3. The system architecture of CNTMS	22
Figure 4. Components of the Query expander	23
Figure 5. An example the distance between two terms	25
Figure 6. The detailed and comprehensive steps running in the Candidate extractor.	28
Figure 7. Translation accuracy of Dataset I by using the phonetic feature	40
Figure 8. Translation accuracy of Dataset II by using the phonetic feature	40
Figure 9. Translation accuracy of Dataset I by using the distant feature	40
Figure 10. Translation accuracy of Dataset II by using the distant feature	40
Figure 11. Translation accuracy of each name type of Dataset I by using the phonetic feature	41
Figure 12. Translation accuracy of each name type of Dataset I by using the distant feature	41
Figure 13. Translation accuracy of each name type of Dataset II by using the phonetic feature	42
Figure 14. Translation accuracy of each name type of Dataset II by using the distant feature	42
Figure 15. Translation accuracy of Dataset I by using both the phonetic and the distant features	45
Figure 16. Translation accuracy of Dataset I by using both the phonetic and the distant features	45
Figure 17. Translation accuracy of each name type of Dataset I by using both the phonetic and the distant features	46
Figure 18. Translation accuracy of each name type of Dataset II by using both the phonetic and the distant features	46

                                

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