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dc.contributor.authorLiu, Duen-Renen_US
dc.contributor.authorLiou, Chuen-Heen_US
dc.date.accessioned2014-12-08T15:37:51Z-
dc.date.available2014-12-08T15:37:51Z-
dc.date.issued2011-01-01en_US
dc.identifier.issn1567-4223en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.elerap.2010.08.004en_US
dc.identifier.urihttp://hdl.handle.net/11536/26029-
dc.description.abstractThe number of third generation (3G) subscribers conducting mobile commerce has increased as mobile data communications have evolved. Multi-channel companies that wish to develop mobile commerce face difficulties due to the lack of knowledge about users' consumption behavior on new mobile channels. Typical collaborative filtering (CF) recommendations may be affected by the so-called sparsity problem because relatively few products are browsed or purchased on the mobile Web. In this study, we propose a hybrid multiple channel method to address the lack of knowledge about users' consumption behavior on a new channel and the difficulty of finding similar users due to the sparsity problem of typical CF recommender systems. Products are recommended to users based on their browsing behavior on the new mobile channel as well as the consumption behavior of heavy users of existing channels, such as television, catalogs, and the Web. Our experiment results show that the proposed method performs well compared to the other recommendation methods. (C) 2010 Elsevier B.V. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectMulti-channel companyen_US
dc.subjectMobile commerceen_US
dc.subjectCollaborative filteringen_US
dc.subjectSparsity problemen_US
dc.subjectHybrid multiple channelsen_US
dc.subjectConsumption behavioren_US
dc.titleMobile commerce product recommendations based on hybrid multiple channelsen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.elerap.2010.08.004en_US
dc.identifier.journalELECTRONIC COMMERCE RESEARCH AND APPLICATIONSen_US
dc.citation.volume10en_US
dc.citation.issue1en_US
dc.citation.spage94en_US
dc.citation.epage104en_US
dc.contributor.department資訊管理與財務金融系 註:原資管所+財金所zh_TW
dc.contributor.departmentDepartment of Information Management and Financeen_US
dc.identifier.wosnumberWOS:000287516300012-
dc.citation.woscount6-
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