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dc.contributor.author이기호*
dc.contributor.author이정원*
dc.date.accessioned2017-11-22T06:30:03Z-
dc.date.available2017-11-22T06:30:03Z-
dc.date.issued2001*
dc.identifier.isbn0769511198*
dc.identifier.isbn9780769511191*
dc.identifier.issn1550-4786*
dc.identifier.otherOAK-18108*
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/239201-
dc.description.abstractXML allows users to define elements using arbitrary words and organize them in a nested structure. These features of XML offer both challenges and opportunities in information retrieval, document management, and data mining. In this paper, we propose a new methodology for preparing XML documents for quantitative determination of similarity between XML documents by taking account of XML semantics (i.e., meanings of the elements and nested structures of XML documents). Accurate quantitative determination of similarity between XML documents provides an important basis for a variety of applications of XML document mining and processing. Experiments with XML documents show that our methodology provides a 50-100% improvement in determining similarity, over the traditional vector-space model that considers only term-frequency and 100% accuracy in identifying the category of each document from an on-line bookstore. © 2001 IEEE.*
dc.description.sponsorshipIEEE Comput. Soc. Tech. Comm. Pattern Anal. Mach. Intell.;IEEE Computer Society Task Force on Virtual Intelligence;Insightful Corporation;Microsoft Research;NARAX Inc.*
dc.languageEnglish*
dc.titlePreparations for semantics-based XML mining*
dc.typeConference Paper*
dc.relation.indexSCOPUS*
dc.relation.startpage345*
dc.relation.lastpage352*
dc.relation.journaltitleProceedings - IEEE International Conference on Data Mining, ICDM*
dc.identifier.scopusid2-s2.0-78149305125*
dc.author.googleLee J.-W.*
dc.author.googleLee K.*
dc.author.googleKim W.*
dc.contributor.scopusid이기호(36617592800)*
dc.date.modifydate20240325112234*
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인공지능대학 > 컴퓨터공학과 > Journal papers
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