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Article: Recommender system based on workflow

TitleRecommender system based on workflow
Authors
KeywordsCollaborative filtering
Knowledge management
Recommender system
Workflow
Issue Date2009
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/dss
Citation
Decision Support Systems, 2009, v. 48 n. 1, p. 237-245 How to Cite?
AbstractThis paper proposes a workflow-based recommender system model on supplying proper knowledge to proper members in collaborative team contexts rather than daily life scenarios, e.g., recommending commodities, films, news, etc. Within collaborative team contexts, more information could be utilized by recommender systems than ordinary daily life contexts. The workflow in collaborative team contains information about relationships among members, roles and tasks, which could be combined with collaborative filtering to obtain members' demands for knowledge. In addition, the work schedule information contained in the workflow could also be employed to determine the proper volume of knowledge that should be recommended to each member. In this paper, we investigate the mechanism of the workflow-based recommender system, and conduct a series of experiments referring to several real-world collaborative teams to validate the effectiveness and efficiency of the proposed methods. © 2009 Elsevier B.V. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/74298
ISSN
2015 Impact Factor: 2.604
2015 SCImago Journal Rankings: 2.262
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorZhen, Len_HK
dc.contributor.authorHuang, GQen_HK
dc.contributor.authorJiang, Zen_HK
dc.date.accessioned2010-09-06T06:59:54Z-
dc.date.available2010-09-06T06:59:54Z-
dc.date.issued2009en_HK
dc.identifier.citationDecision Support Systems, 2009, v. 48 n. 1, p. 237-245en_HK
dc.identifier.issn0167-9236en_HK
dc.identifier.urihttp://hdl.handle.net/10722/74298-
dc.description.abstractThis paper proposes a workflow-based recommender system model on supplying proper knowledge to proper members in collaborative team contexts rather than daily life scenarios, e.g., recommending commodities, films, news, etc. Within collaborative team contexts, more information could be utilized by recommender systems than ordinary daily life contexts. The workflow in collaborative team contains information about relationships among members, roles and tasks, which could be combined with collaborative filtering to obtain members' demands for knowledge. In addition, the work schedule information contained in the workflow could also be employed to determine the proper volume of knowledge that should be recommended to each member. In this paper, we investigate the mechanism of the workflow-based recommender system, and conduct a series of experiments referring to several real-world collaborative teams to validate the effectiveness and efficiency of the proposed methods. © 2009 Elsevier B.V. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/dssen_HK
dc.relation.ispartofDecision Support Systemsen_HK
dc.subjectCollaborative filteringen_HK
dc.subjectKnowledge managementen_HK
dc.subjectRecommender systemen_HK
dc.subjectWorkflowen_HK
dc.titleRecommender system based on workflowen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0167-9236&volume=48&issue=1&spage=237&epage=245&date=2009&atitle=Recommender+system+based+on+workflowen_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.dss.2009.08.002en_HK
dc.identifier.scopuseid_2-s2.0-70449127075en_HK
dc.identifier.hkuros169675en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-70449127075&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume48en_HK
dc.identifier.issue1en_HK
dc.identifier.spage237en_HK
dc.identifier.epage245en_HK
dc.identifier.isiWOS:000272366100024-
dc.publisher.placeNetherlandsen_HK
dc.identifier.scopusauthoridZhen, L=14053327700en_HK
dc.identifier.scopusauthoridHuang, GQ=7403425048en_HK
dc.identifier.scopusauthoridJiang, Z=35240389200en_HK
dc.identifier.citeulike5686977-

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