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Fusing hotel ratings and reviews with hesitant terms and consensus measures

Author
Nguyen, J.; Montserrat, J.; Agell, N.; Sanchez, M.; Ruiz, F.
Type of activity
Journal article
Journal
Neural computing and applications
Date of publication
2020-02-27
Volume
32
First page
15301
Last page
15311
DOI
10.1007/s00521-020-04778-x
Project funding
Analysis of “shared value” iniciatives for SME: Multi-criteria decision aid approaches under uncertainty
Mathematical structures for linguistic assessments in decision processess: advanced solutions for tourism management in smart cities
Repository
http://hdl.handle.net/2117/330410 Open in new window
URL
https://link.springer.com/article/10.1007%2Fs00521-020-04778-x Open in new window
Abstract
People have come to refer to reviews for valuable information on products before making a purchase. Digesting relevant opinions regarding a product by reading all the reviews is challenging. An automated methodology which aggregates opinions across all the reviews for a single product to help differentiate any two products having the same overall rating is defined. In order to facilitate this process, rating values, which capture the overall satisfaction, and written reviews, which contain the s...
Citation
Nguyen, J. [et al.]. Fusing hotel ratings and reviews with hesitant terms and consensus measures. "Neural computing and applications", 27 Febrer 2020, vol. 32, p. 15301-15311.
Keywords
Consensus models, Hesitant fuzzy linguistic term sets, Linguistic decision making, Reviews, Tourism
Group of research
GREC - Knowledge Engineering Research Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

Participants