A Muti-Resolution Approach to Restaurant Named Entity Recognition in KoreanWeb
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kang, Bo-Yeong | - |
dc.contributor.author | Kim, Dae-Won | - |
dc.date.available | 2019-06-26T01:19:25Z | - |
dc.date.issued | 2012-12 | - |
dc.identifier.issn | 1598-2645 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/26093 | - |
dc.description.abstract | Named 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.extent | 8 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | 한국지능시스템학회 | - |
dc.title | A Muti-Resolution Approach to Restaurant Named Entity Recognition in KoreanWeb | - |
dc.type | Article | - |
dc.identifier.bibliographicCitation | International Journal of Fuzzy Logic and Intelligent systems, v.12, no.4, pp 277 - 284 | - |
dc.identifier.kciid | ART001721685 | - |
dc.description.isOpenAccess | N | - |
dc.citation.endPage | 284 | - |
dc.citation.number | 4 | - |
dc.citation.startPage | 277 | - |
dc.citation.title | International Journal of Fuzzy Logic and Intelligent systems | - |
dc.citation.volume | 12 | - |
dc.publisher.location | 대한민국 | - |
dc.subject.keywordAuthor | Named entity classification | - |
dc.subject.keywordAuthor | semantic feature | - |
dc.subject.keywordAuthor | multi-resolution approach | - |
dc.description.journalRegisteredClass | kci | - |
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