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An Effective Hotel Recommendation System through Processing Heterogeneous Data

Version 2 2023-12-21, 01:27
Version 1 2021-08-13, 01:52
journal contribution
posted on 2023-12-21, 01:27 authored by Md Shafiul Alam Forhad, Mohammad Shamsul Arefin, A S M KayesA S M Kayes, Khandakar Ahmed, Mohammad Jabed Morshed ChowdhuryMohammad Jabed Morshed Chowdhury, Indika Kumara
Recommendation systems have recently gained a lot of popularity in various industries such as entertainment and tourism. They can act as filters of information by providing relevant suggestions to the users through processing heterogeneous data from different networks. Many travelers and tourists routinely rely on textual reviews, numerical ratings, and points of interest to select hotels in cities worldwide. To attract more customers, online hotel booking systems typically rank their hotels based on the recommendations from their customers. In this paper, we present a framework that can rank hotels by analyzing hotels’ customer reviews and nearby amenities. In addition, a framework is presented that combines the scores generated from user reviews and surrounding facilities. We perform experiments using datasets from online hotel booking platforms such as TripAdvisor and Booking to evaluate the effectiveness and applicability of the proposed framework. We first store the keywords extracted from reviews and assign weights to each considered unigram and bigram keywords and, then, we give a numerical score to each considered keyword. Finally, our proposed system aggregates the scores generated from the reviews and surrounding environments from different categories of the facilities. Experimental results confirm the effectiveness of the proposed recommendation framework.

History

Publication Date

2021-08-10

Journal

Electronics

Volume

10

Issue

16

Pagination

(p. 1920-1920)

Publisher

MDPI AG

Rights Statement

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

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