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dc.contributor.author최용석-
dc.date.accessioned2018-04-03T07:08:31Z-
dc.date.available2018-04-03T07:08:31Z-
dc.date.issued2014-10-
dc.identifier.citationProceedings of the 2014 Research in Adaptive and Convergent Systems, RACS 2014. (Proceedings of the 2014 Research in Adaptive and Convergent Systems, RACS 2014, 5 October 2014, p.72-76en_US
dc.identifier.isbn978-1-4503-3060-2-
dc.identifier.urihttps://dl.acm.org/citation.cfm?id=2664189-
dc.identifier.urihttp://hdl.handle.net/20.500.11754/56982-
dc.description.abstractIn this paper, we propose content-metadata based combined approach to effective collaborative recommendation. Our approach combines user-item rating scores and/or trust network information with content-metadata compensatively for boosting collaborative recommendation. In experiment, we identified that our approach could considerably improve recommendation performance when compared to existing collaborative recommendation methods.en_US
dc.description.sponsorshipThis work was supported by Samsung Electronics Company and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2012R1A1A2001039). This research was supported by the MSIP Korea, under the ITRC support program (NIPA-2014-H0301-14-1017) supervised by the NIPA.en_US
dc.language.isoenen_US
dc.publisherAssociation for Computing Machinery, Incen_US
dc.subjectcollaborative recommendationen_US
dc.subjectcombined approachen_US
dc.subjectcontent metadataen_US
dc.titleMetadata Based Combined Approach for Effective Collaborative Recommendationen_US
dc.typeArticleen_US
dc.identifier.doi10.1145/2663761.2664189-
dc.relation.page72-77-
dc.contributor.googleauthorKim, Kyung Soo-
dc.contributor.googleauthorLee, Jun Yeop-
dc.contributor.googleauthorChoi, Yong Suk-
dc.relation.code20140083-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF ENGINEERING[S]-
dc.sector.departmentDEPARTMENT OF COMPUTER SCIENCE-
dc.identifier.pidcys-
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COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
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