頁籤選單縮合
題 名 | Improving Translation of Queries with Infrequent Unknown Abbreviations and Proper Names |
---|---|
作 者 | Lu, Wen-hsiang; Lin, Jiun-hung; Chang, Yao-sheng; | 書刊名 | International Journal of Computational Linguistics & Chinese Language Processing |
卷 期 | 13:1 2008.03[民97.03] |
頁 次 | 頁91-119 |
分類號 | 312.23 |
關鍵詞 | CLIR; Transliteration; Unknown term translation; Web search result; Machine translation; |
語 文 | 英文(English) |
英文摘要 | Unknown term translation is important to CLIR and MT systems, but it is still an unsolved problem. Recently, a few researchers have proposed several effective search-result-based term translation extraction methods which explore search results to discover translations of frequent unknown terms from Web search results. However, many infrequent unknown terms, such as abbreviations and proper names (or named entities), and their translations are still difficult to be obtained using these methods. Therefore, in this paper we present a new search-result-based abbreviation translation method and a new two-stage hybrid translation extraction method to solve the problem of extracting translations of infrequent unknown abbreviations and proper names from Web search results. In addition, to efficiently apply name transliteration techniques to mitigate the problems of proper name translation, we propose a mixed-syllable-mapping transliteration model and a Web-based unsupervised learning algorithm for dealing with online English-Chinese name transliteration. Our experimental results show that our proposed new methods can make great improvements compared with the previous search-result-based term translation extraction methods. |
本系統中英文摘要資訊取自各篇刊載內容。