Cross-Language Information Retrieval
Encyclopedia of Machine Learning and Data MiningPublished 1 January 2017
Claude Sammut, Geoffrey I. Webb
Citations246
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TL;DR
This chapter reviews research and practice in CLIR that allows users to state queries in their native language and retrieve documents in any other language supported by the system.
Abstract
This article addresses a timely problem, especially within the context of the Internet, which is accessible by anyone in any discipline from virtually anywhere in the world. The problem of cross-language retrieval is not new. Then at now, cross-language information retrieval was seen to be a function that would facilitate the effective search for, exchange of, and retrieval information. This chapter reviews research and practice in CLIR that allows users to state queries in their native language and retrieve documents in any other language supported by the system. CLIR can simplify searching by multilingual users and, if translation resources are limited, can allow monolingual users to allocate those resources to the more promising documents. This review begins with an examination of the literature on user needs for CLIR. The chapter largely follows the retrieval system model (document preprocessing, query formulation, matching, selection, and delivery). Each section highlights the unique requirements imposed on one more stages of the model in cross-language retrieval applications. The authors describe evaluation techniques and conclude with observations regarding future directions for CLIR research.
Keywords
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