An effective hotel recommendation system through processing heterogeneous data

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Forhad, Md. Shafiul Alam ORCID: 0000-0002-0538-4571, Arefin, Mohammad Shamsul ORCID: 0000-0003-0259-7624, Kayes, ASM ORCID: 0000-0002-2421-2214, Ahmed, Khandakar ORCID: 0000-0003-1043-2029, Chowdhury, Mohammad Jabed Morshed and Kumara, Indika (2021) An effective hotel recommendation system through processing heterogeneous data. Electronics, 10 (16). ISSN 2079-9292

Abstract

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.

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/44352
DOI https://doi.org/10.3390/electronics10161920
Official URL https://www.mdpi.com/2079-9292/10/16/1920
Subjects Current > FOR (2020) Classification > 3508 Tourism
Current > FOR (2020) Classification > 4602 Artificial intelligence
Current > FOR (2020) Classification > 4605 Data management and data science
Current > Division/Research > College of Science and Engineering
Keywords automated recommendation, hotel booking system, heterogeneous network data, data processing, points of interest, review analysis, score generation
Citations in Scopus 3 - View on Scopus
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