Improving cross language information retrieval using corpus based query suggestion approach

Show simple item record Prasath, Rajendra Sarkar, Sudeshna O'Reilly, Philip
dc.contributor.editor Gelbukh, Alexander 2016-09-20T10:39:36Z 2016-09-20T10:39:36Z 2015-04
dc.identifier.citation Prasath, R., Sarkar, S. and O'Reilly, P. (2015) 'Improving cross language information retrieval using corpus based query suggestion approach', in Gelbukh, A. (ed.) CICLing 2015, Part II, Lecture Notes in Computer Science, 9042, pp. 448–457. doi: 10.1007/978-3-319-18117-2_33 en
dc.identifier.volume 9042 en
dc.identifier.startpage 448 en
dc.identifier.endpage 457 en
dc.identifier.doi 10.1007/978-3-319-18117-2_33
dc.description.abstract Users seeking information may not find relevant information pertaining to their information need in a specific language. But information may be available in a language different from their own, but users may not know that language. Thus users may experience difficulty in accessing the information present in different languages. Since the retrieval process depends on the translation of the user query, there are many issues in getting the right translation of the user query. For a pair of languages chosen by a user, resources, like incomplete dictionary, inaccurate machine translation system may exist. These resources may be insufficient to map the query terms in one language to its equivalent terms in another language. Also for a given query, there might exist multiple correct translations. The underlying corpus evidence may suggest a clue to select a probable set of translations that could eventually perform a better information retrieval. In this paper, we present a cross language information retrieval approach to effectively retrieve information present in a language other than the language of the user query using the corpus driven query suggestion approach. The idea is to utilize the corpus based evidence of one language to improve the retrieval and re-ranking of news documents in the other language. We use FIRE corpora - Tamil and English news collections in our experiments and illustrate the effectiveness of the proposed cross language information retrieval approach. en
dc.description.sponsorship R14903 en
dc.description.uri en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Springer International Publishing en
dc.relation.ispartof CICLing 2015, Part II, Lecture Notes in Computer Science, vol. 9042
dc.rights © 2015, Springer International Publishing, Switzerland. The final publication is available at Springer via en
dc.subject Query suggestion en
dc.subject Corpus statistics en
dc.subject Retrieval efficiency en
dc.subject Cross-lingual document retrieval en
dc.title Improving cross language information retrieval using corpus based query suggestion approach en
dc.type Conference item en
dc.internal.authorcontactother Rajendra Prasath, Business Information Systems, University College Cork, Cork, Ireland. +353-21-490-3000 Email: en
dc.internal.availability Full text available en 2015-04-06T19:24:50Z
dc.description.version Accepted Version en
dc.internal.rssid 297002466
dc.description.status Peer reviewed en
dc.identifier.journaltitle Lecture Notes in Computer Science en
dc.internal.copyrightchecked No en
dc.internal.licenseacceptance Yes en
dc.internal.conferencelocation Egypt en
dc.internal.IRISemailaddress en

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