A web-aided query translation expansion method in Cross-Language Information Retrieval (CLIR) is presented in this study. The method is applied to English/Chinese language pair, in which queries are expressed in English and the documents returned are in Chinese. Among the three main categories of CLIR methods of machine translation (MT), dictionary translation using a machine-readable dictionary (MRD), and parallel corpus, our method is based on the second one. MRD-based method is easy to implement. However, it faces the resource limitation problem, i.e., the dictionary is often incomplete leading to poor translation and hence undesirable results. By combining MRD and web-aided query translation expansion technique, good retrieval performance can be achieved. The performance gain is largely due to the successful translation extraction of relevant words of a query term from online texts. A new Chinese word discovery algorithm, which extracts words from continuous Chinese characters was designed and used for this purpose. The extracted relevant words do not only include the precise translation of a query term, but also those words that are relevant to that term in the source language. / Jin Honglan. / "October 2005." / Adviser: Kam Fai Wong. / Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 3899. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (p. 115-121). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract in English and Chinese. / School code: 1307.
Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_343665 |
Date | January 2005 |
Contributors | Jin, Honglan., Chinese University of Hong Kong Graduate School. Division of Systems Engineering and Engineering Management. |
Source Sets | The Chinese University of Hong Kong |
Language | English, Chinese |
Detected Language | English |
Type | Text, theses |
Format | electronic resource, microform, microfiche, 1 online resource (v, 121 p. : ill.) |
Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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