DC Field | Value | Language |
---|---|---|
dc.contributor.author | 장명하 | en_US |
dc.date.accessioned | 2014-12-01T11:48:18Z | - |
dc.date.available | 2014-12-01T11:48:18Z | - |
dc.date.issued | 2012 | en_US |
dc.identifier.other | OAK-2014-01151 | en_US |
dc.identifier.uri | http://postech.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000001390024 | en_US |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/1653 | - |
dc.description | Master | en_US |
dc.description.abstract | Comparing 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.language | eng | en_US |
dc.publisher | 포항공과대학교 | en_US |
dc.rights | BY_NC_ND | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/2.0/kr | en_US |
dc.title | Mining Comparable Entities from the Web | en_US |
dc.type | Thesis | en_US |
dc.contributor.college | 일반대학원 컴퓨터공학과 | en_US |
dc.date.degree | 2012- 8 | en_US |
dc.contributor.department | 포항공과대학교 | en_US |
dc.type.docType | Thesis | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
library@postech.ac.kr Tel: 054-279-2548
Copyrights © by 2017 Pohang University of Science ad Technology All right reserved.