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A Muti-Resolution Approach to Restaurant Named Entity Recognition in KoreanWeb

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dc.contributor.authorKang, Bo-Yeong-
dc.contributor.authorKim, Dae-Won-
dc.date.available2019-06-26T01:19:25Z-
dc.date.issued2012-12-
dc.identifier.issn1598-2645-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/26093-
dc.description.abstractNamed entity recognition (NER) technique can play a crucial role in extracting information from the web. While NER systems with relatively high performances have been developed based on careful manipulation of terms with a statistical model, term mismatches often degrade the performance of such systems because the strings of all the candidate entities are not known a priori. Despite the importance of lexical-level term mismatches for NER systems, however, most NER approaches developed to date utilize only the term string itself and simple term-level features, and do not exploit the semantic features of terms which can handle the variations of terms effectively. As a solution to this problem, here we propose to match the semantic concepts of term units in restaurant named entities (NEs), where these units are automatically generated from multiple resolutions of a semantic tree. As a test experiment, we applied our restaurant NER scheme to 49,153 nouns in Korean restaurant web pages. Our scheme achieved an average accuracy of 87.89% when applied to test data, which was considerably better than the 78.70% accuracy obtained using the baseline system.-
dc.format.extent8-
dc.language영어-
dc.language.isoENG-
dc.publisher한국지능시스템학회-
dc.titleA Muti-Resolution Approach to Restaurant Named Entity Recognition in KoreanWeb-
dc.typeArticle-
dc.identifier.bibliographicCitationInternational Journal of Fuzzy Logic and Intelligent systems, v.12, no.4, pp 277 - 284-
dc.identifier.kciidART001721685-
dc.description.isOpenAccessN-
dc.citation.endPage284-
dc.citation.number4-
dc.citation.startPage277-
dc.citation.titleInternational Journal of Fuzzy Logic and Intelligent systems-
dc.citation.volume12-
dc.publisher.location대한민국-
dc.subject.keywordAuthorNamed entity classification-
dc.subject.keywordAuthorsemantic feature-
dc.subject.keywordAuthormulti-resolution approach-
dc.description.journalRegisteredClasskci-
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소프트웨어대학 (소프트웨어학부)
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