Ubiquitous Hotel Recommendation Using a Fuzzy-Weighted-Average and Backpropagation-Network Approach

Tin-Chih Chen*

*Corresponding author for this work

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Ubiquitous 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.

Original languageEnglish
Pages (from-to)316-341
Number of pages26
JournalInternational Journal of Intelligent Systems
Volume32
Issue number4
DOIs
StatePublished - 1 Apr 2017

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