4.5 Article

Consumer recommendation prediction in online reviews using Cuckoo optimized machine learning models

Journal

COMPUTERS & ELECTRICAL ENGINEERING
Volume 95, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compeleceng.2021.107397

Keywords

Online reviews; Cuckoo Search; Machine learning; Sentiment analysis; Recommendation prediction; Extreme gradient boosting

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Digital technology and social media offer many advantages in understanding human psychology, particularly for industrial growth. In online reviews, consumer recommendations are critical for service providers to enhance consumer policies and service quality.
Digital technology and social media have delivered many advantages in understanding human psychology, which is essential to industrial growth. Skytrax is an online social media platform for travellers to write reviews on airlines. In online reviews, consumer recommendations are critical indicators for service providers to improve their consumer policies as well as service quality. It is also helpful for future customers to help get information on future purchases prior to making them. Therefore, previous consumer recommendations based on online reviews play a vital role in airline recommendations. Our main goal is to use our proposed cuckoo optimized machine learning model to predict airline recommendations. Experimental analysis was implemented using data scraped from the website https://www.airlinequality.com. Our results show that the proposed eXtreme gradient boosting classifier optimized by Cuckoo Search (CS-XGB) outperforms other state-of-the-art techniques.

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