Bidirectional LSTM Model in Predicting Satisfaction Level of Passengers on Airline Service
Author:
Affiliation:
1. School of Mathematics Shanghai Jiao Tong University,Shanghai,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9797458/9797460/09797466.pdf?arnumber=9797466
Reference10 articles.
1. Impact of Covid-19 on passengers and airlines from passenger measurements: Managing customer satisfaction while putting the US Air Transportation System to sleep
2. Passenger satisfaction with airline service quality in Malaysia: A structural equation modeling approach
3. AdaBoost typical Algorithm and its application research
4. Advanced Classification Method of Twitter Data using Sentiment Analysis for Airline Service;hemakala;International Journal of Computational Engineering Science,2018
5. A machine learning approach to analyze customer satisfaction from airline tweets
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1. Forecasting airline passengers’ satisfaction based on sentiments and ratings: An application of VADER and machine learning techniques;Journal of Air Transport Management;2024-09
2. Explainable Stacking Machine Learning Ensemble for Predicting Airline Customer Satisfaction;Third Congress on Intelligent Systems;2023
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