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Hotel Quality Evaluation from Online Reviews Using Fuzzy Pattern Matching and Fuzzy Cognitive Maps

Authors:
Alexandros Bousdekis
Dimitris Kardaras
Stavroula Barbounaki

Keywords: e-tourism; data analytics; machine learning; tourism management; service quality

Abstract:
Online review comments have become a popular and efficient way for sellers to acquire feedback from customers and improve their service quality. These online reviews in the e-tourism era, in the format of both textual reviews (comments) and ratings, generate an electronic Word Of Mouth (eWOM) effect, which influences future customer demand and hotels’ financial performance and thus have significant business value. This paper proposes an approach for hotel quality evaluation according to online review comments and ratings using Fuzzy Pattern Matching (FPM) for mining customers’ opinions and Fuzzy Cognitive Maps (FCM) for evaluating the attributes that contribute to the review rating. The proposed approach was applied to a 4-star hotels dataset in Athens, Greece and experiments were performed.

Pages: 61 to 66

Copyright: Copyright (c) IARIA, 2020

Publication date: October 25, 2020

Published in: conference

ISSN: 2308-4464

ISBN: 978-1-61208-816-7

Location: Nice, France

Dates: from October 25, 2020 to October 29, 2020