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dc.contributor.authorChen, Tolyen_US
dc.date.accessioned2018-08-21T05:52:46Z-
dc.date.available2018-08-21T05:52:46Z-
dc.date.issued2017-04-01en_US
dc.identifier.issn0884-8173en_US
dc.identifier.urihttp://dx.doi.org/10.1002/int.21863en_US
dc.identifier.urihttp://hdl.handle.net/11536/143931-
dc.description.abstractUbiquitous hotel recommendation is a highly popular type of location- aware service. However, existing recommendation systems have several problems. This paper proposes a fuzzy-weighted-average (FWA) and backpropagation-network (BPN) approach for overcoming the hindrances of ubiquitous hotel recommendation and improving its effectiveness, whereby FWA is applied to evaluate the overall performance of a hotel. A BPN was constructed to defuzzify the overall performance. In addition, the personally preferred index is proposed for addressing the traveler choices of a dominated hotel. The effectiveness of the proposed methodology was tested using a field study in a small region in Seatwen, Taichung City, Taiwan.(C) 2016 Wiley Periodicals, Inc.en_US
dc.language.isoen_USen_US
dc.titleUbiquitous Hotel Recommendation Using a Fuzzy-Weighted-Average and Backpropagation-Network Approachen_US
dc.typeArticleen_US
dc.identifier.doi10.1002/int.21863en_US
dc.identifier.journalINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMSen_US
dc.citation.volume32en_US
dc.contributor.department工業工程與管理學系zh_TW
dc.contributor.departmentDepartment of Industrial Engineering and Managementen_US
dc.identifier.wosnumberWOS:000394896500002en_US
Appears in Collections:Articles