Enhancing Minority Sentiment Classification in Gastronomy Tourism: A Hybrid Sentiment Analysis Framework With Data Augmentation, Feature Engineering and Business Intelligence

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Enhancing Minority Sentiment Classification in Gastronomy Tourism: A Hybrid Sentiment Analysis Framework With Data Augmentation, Feature Engineering and Business Intelligence

The gastronomy tourism industry plays an important role in boosting local economies, enhancing the travel experience, and preserving culinary traditions unique to specific places. In this context, comprehending customer sentiments is of paramount importance for business decision-making, menu choice...

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Bibliographic Details
Published in:	IEEE ACCESS
Main Authors:	Razali, Mohd Norhisham; Manaf, Syaifulnizam Abdul; Hanapi, Rozita Binti; Salji, Mohd Rafiz; Chiat, Lee Wen; Nisar, Kashif
Format:	Article
Language:	English
Published:	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC 2024
Subjects:	Computer Science; Engineering; Telecommunications
Online Access:	https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001199995100001

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