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Titlebook: Cross-Language Information Retrieval; Gregory Grefenstette Book 1998 Springer Science+Business Media New York 1998 corpus.database.filteri

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21#
發(fā)表于 2025-3-25 06:27:36 | 只看該作者
The Problem of Cross-Language Information Retrieval,on access, it becomes more common for non-native speakers to explore multilingual text collections. Beyond merely accepting 8-bit accented characters, information retrieval systems should provide help in searching for information across language boundaries. This situation has given rise to a new res
22#
發(fā)表于 2025-3-25 11:05:35 | 只看該作者
23#
發(fā)表于 2025-3-25 13:34:21 | 只看該作者
24#
發(fā)表于 2025-3-25 19:06:18 | 只看該作者
25#
發(fā)表于 2025-3-25 23:33:02 | 只看該作者
26#
發(fā)表于 2025-3-26 03:35:18 | 只看該作者
Mapping Vocabularies Using Latent Semantics,hen confronted with systems that rely on standardized language, such as MeSH, SNOMED, or ICD, and the special terms sets of systems such as HELP, INTERNIST-I/QMR, and DXplain. Indeed, the need to map natural language into appropriate special terms—as well as the need to map one system’s specialized
27#
發(fā)表于 2025-3-26 05:07:52 | 只看該作者
28#
發(fā)表于 2025-3-26 09:21:05 | 只看該作者
A Language Conversion Front-End for Cross-Language Information Retrieval,tion methods developed for machine translation systems, and is a combination of a statistics-based word selection method where statistical information is extracted from non-parallel corpora, and an interactive user interface to improve the translation quality. We describe its implementation as a fro
29#
發(fā)表于 2025-3-26 15:39:17 | 只看該作者
The Systran NLP Browser: An Application of Machine Translation Technology in Cross-Language Informaranslating queries, or even the entire textual database, from one language to another. The information that machine translation technology can provide to cross-language information retrieval has been more extensively explored at SYSTRAN. This chapter is a description of the implementation of SYSTRAN
30#
發(fā)表于 2025-3-26 20:04:38 | 只看該作者
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