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dc.contributor.author장명하en_US
dc.date.accessioned2014-12-01T11:48:18Z-
dc.date.available2014-12-01T11:48:18Z-
dc.date.issued2012en_US
dc.identifier.otherOAK-2014-01151en_US
dc.identifier.urihttp://postech.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000001390024en_US
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/1653-
dc.descriptionMasteren_US
dc.description.abstractComparing entities is an important part of decision making. Several approaches have been reported for mining comparable entities from Web sources to improve user experience in comparing entities online. However, these efforts extract only entities explicitly compared in the corpora, and may exclude entities that occur less-frequently but potentially comparable.To build a more complete comparison machine that caninfer such missing relations, here we develop a solution to predict transitivity of known comparable relations. Named CliqueGrow, our approach predicts missing linksgiven a comparable entity graph obtained from versus query logs.Our approach achieved the highest F1-score amongfive link prediction approaches and a commercial comparison engine provided by Yahoo!.en_US
dc.languageengen_US
dc.publisher포항공과대학교en_US
dc.rightsBY_NC_NDen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.0/kren_US
dc.titleMining Comparable Entities from the Weben_US
dc.typeThesisen_US
dc.contributor.college일반대학원 컴퓨터공학과en_US
dc.date.degree2012- 8en_US
dc.contributor.department포항공과대학교en_US
dc.type.docTypeThesis-

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