Consumer recommendation prediction in online reviews using Cuckoo optimized machine learning models. (October 2021)
- Record Type:
- Journal Article
- Title:
- Consumer recommendation prediction in online reviews using Cuckoo optimized machine learning models. (October 2021)
- Main Title:
- Consumer recommendation prediction in online reviews using Cuckoo optimized machine learning models
- Authors:
- Jain, Praphula Kumar
Yekun, Ephrem Admasu
Pamula, Rajendra
Srivastava, Gautam - Abstract:
- Abstract: 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. Graphical abstract: Highlights: Propose a consumer recommendation prediction system using online review. Acquired consumer online reviews and ratings from Skytrax. Applied various pre-processing schemes to input data and feed it to the model. Create a Cuckoo Search (CS) based parameter optimization model. Proposed CS-XGB outperforms the other state-of-the-art techniques.
- Is Part Of:
- Computers & electrical engineering. Volume 95(2021)
- Journal:
- Computers & electrical engineering
- Issue:
- Volume 95(2021)
- Issue Display:
- Volume 95, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 95
- Issue:
- 2021
- Issue Sort Value:
- 2021-0095-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-10
- Subjects:
- Online reviews -- Cuckoo Search -- Machine learning -- Sentiment analysis -- Recommendation prediction -- Extreme gradient boosting
Computer engineering -- Periodicals
Electrical engineering -- Periodicals
Electrical engineering -- Data processing -- Periodicals
Ordinateurs -- Conception et construction -- Périodiques
Électrotechnique -- Périodiques
Électrotechnique -- Informatique -- Périodiques
Computer engineering
Electrical engineering
Electrical engineering -- Data processing
Periodicals
Electronic journals
621.302854 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00457906/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compeleceng.2021.107397 ↗
- Languages:
- English
- ISSNs:
- 0045-7906
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.680000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 19347.xml