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Article: An inner-enterprise knowledge recommender system

TitleAn inner-enterprise knowledge recommender system
Authors
KeywordsContext awareness
Knowledge management
Recommender system
Issue Date2010
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/eswa
Citation
Expert Systems With Applications, 2010, v. 37 n. 2, p. 1703-1712 How to Cite?
AbstractThis paper proposes a model of the inner-enterprise knowledge recommender system. Among an organization, different members have different demands for knowledge in different context. Comparing with traditional knowledge query way, the knowledge recommender systems supply us a more proactive way that could deliver the proper knowledge to the proper people at the proper time. The recommendation mechanism is based on semantic matching on context information from both users' side and knowledge's side. Recommendation rules are also maintained in the recommendation engine, which is the core module in the system. By adjusting the rules, the configuration of the knowledge recommender system could be adapted to different users. This paper presents the system design as well as some key technologies analysis, and also discusses the advantages and preconditions for implementing the proposed system. © 2009 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/74338
ISSN
2015 Impact Factor: 2.981
2015 SCImago Journal Rankings: 1.839
ISI Accession Number ID
Funding AgencyGrant Number
973/National Basic Research Program2003CB317005
Funding Information:

This work is also partially supported by the 973/National Basic Research Program (2003CB317005).

References

 

DC FieldValueLanguage
dc.contributor.authorZhen, Len_HK
dc.contributor.authorHuang, GQen_HK
dc.contributor.authorJiang, Zen_HK
dc.date.accessioned2010-09-06T07:00:21Z-
dc.date.available2010-09-06T07:00:21Z-
dc.date.issued2010en_HK
dc.identifier.citationExpert Systems With Applications, 2010, v. 37 n. 2, p. 1703-1712en_HK
dc.identifier.issn0957-4174en_HK
dc.identifier.urihttp://hdl.handle.net/10722/74338-
dc.description.abstractThis paper proposes a model of the inner-enterprise knowledge recommender system. Among an organization, different members have different demands for knowledge in different context. Comparing with traditional knowledge query way, the knowledge recommender systems supply us a more proactive way that could deliver the proper knowledge to the proper people at the proper time. The recommendation mechanism is based on semantic matching on context information from both users' side and knowledge's side. Recommendation rules are also maintained in the recommendation engine, which is the core module in the system. By adjusting the rules, the configuration of the knowledge recommender system could be adapted to different users. This paper presents the system design as well as some key technologies analysis, and also discusses the advantages and preconditions for implementing the proposed system. © 2009 Elsevier Ltd. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/eswaen_HK
dc.relation.ispartofExpert Systems with Applicationsen_HK
dc.subjectContext awarenessen_HK
dc.subjectKnowledge managementen_HK
dc.subjectRecommender systemen_HK
dc.titleAn inner-enterprise knowledge recommender systemen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0957-4174&volume=&spage=&epage=&date=2009&atitle=An+inner-enterprise+knowledge+recommender+system+en_HK
dc.identifier.emailHuang, GQ:gqhuang@hkucc.hku.hken_HK
dc.identifier.authorityHuang, GQ=rp00118en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.eswa.2009.06.057en_HK
dc.identifier.scopuseid_2-s2.0-71749085231en_HK
dc.identifier.hkuros163353en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-71749085231&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume37en_HK
dc.identifier.issue2en_HK
dc.identifier.spage1703en_HK
dc.identifier.epage1712en_HK
dc.identifier.isiWOS:000272432300093-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridZhen, L=14053327700en_HK
dc.identifier.scopusauthoridHuang, GQ=7403425048en_HK
dc.identifier.scopusauthoridJiang, Z=35240389200en_HK
dc.identifier.citeulike5184221-

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