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Matching meaning for cross-language ...
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Wang, Jianqiang.
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Matching meaning for cross-language information retrieval.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Matching meaning for cross-language information retrieval./
作者:
Wang, Jianqiang.
面頁冊數:
209 p.
附註:
Source: Dissertation Abstracts International, Volume: 66-12, Section: A, page: 4220.
Contained By:
Dissertation Abstracts International66-12A.
標題:
Information Science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3202413
ISBN:
9780542475078
Matching meaning for cross-language information retrieval.
Wang, Jianqiang.
Matching meaning for cross-language information retrieval.
- 209 p.
Source: Dissertation Abstracts International, Volume: 66-12, Section: A, page: 4220.
Thesis (Ph.D.)--University of Maryland, College Park, 2005.
Cross-language information retrieval concerns the problem of finding information in one language in response to search requests expressed in another language. The explosive growth of the World Wide Web, with access to information in many languages, has provided a substantial impetus for research on this important problem. In recent years, significant advances in cross-language retrieval effectiveness have resulted from the application of statistical techniques to estimate accurate translation probabilities for individual terms from automated analysis of human-prepared translations. With few exceptions, however, those results have been obtained by applying evidence about the meaning of terms to translation in one direction at a time (e.g., by translating the queries into the document language).
ISBN: 9780542475078Subjects--Topical Terms:
1017528
Information Science.
Matching meaning for cross-language information retrieval.
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Cross-language information retrieval concerns the problem of finding information in one language in response to search requests expressed in another language. The explosive growth of the World Wide Web, with access to information in many languages, has provided a substantial impetus for research on this important problem. In recent years, significant advances in cross-language retrieval effectiveness have resulted from the application of statistical techniques to estimate accurate translation probabilities for individual terms from automated analysis of human-prepared translations. With few exceptions, however, those results have been obtained by applying evidence about the meaning of terms to translation in one direction at a time (e.g., by translating the queries into the document language).
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This dissertation introduces a more general framework for the use of translation probability in cross-language information retrieval based on the notion that information retrieval is dependent fundamentally upon matching what the searcher means with what the document author meant. The perspective yields a simple computational formulation that provides a natural way of combining what have been known traditionally as query and document translation. When combined with the use of synonym sets as a computational model of meaning, cross-language search results are obtained using English queries that approximate a strong monolingual baseline for both French and Chinese documents. Two well-known techniques (structured queries and probabilistic structured queries) are also shown to be a special case of this model under restrictive assumptions.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3202413
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