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Identifying key drivers in airline recommendations using logistic regression from web scraping

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Praowpan TansitpongAuthors Info & Claims

ICCMB '20: Proceedings of the 2020 the 3rd International Conference on Computers in Management and Business

Pages 112 - 116

https://doi.org/10.1145/3383845.3383870

Published: 05 April 2020 Publication History

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Abstract

This study explores key determinants of airline recommendations from online reviews. By using online web scraping information, this study is able to distinguish recommenders from non-recommenders from online reviews. This study further builds a prediction model for airline recommenders from service by using logistic regression to characterize features on how passengers decide to recommend other.

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Cited By

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Wang JMei HLi KZhang XChen X(2023)Collaborative Filtering Model of Graph Neural Network Based on Random WalkApplied Sciences10.3390/app1303178613:3(1786)Online publication date: 30-Jan-2023
https://doi.org/10.3390/app13031786
Mundargi ZMulay SNavale DTalnikar VNawale ASonkusale V(2023)An Aviation Industry Recommender System(AIRS) using K-nearest Neighbour and Cosine Similarity2023 International Conference for Advancement in Technology (ICONAT)10.1109/ICONAT57137.2023.10080009(1-6)Online publication date: 24-Jan-2023
https://doi.org/10.1109/ICONAT57137.2023.10080009

Index Terms

Identifying key drivers in airline recommendations using logistic regression from web scraping
1. Applied computing
  1. Operations research
    1. Marketing

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ICCMB '20: Proceedings of the 2020 the 3rd International Conference on Computers in Management and Business

January 2020

303 pages

ISBN:9781450376778

DOI:10.1145/3383845

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Univ. of Manchester: University of Manchester
The Hong Kong Polytechnic: The Hong Kong Polytechnic University

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Association for Computing Machinery

New York, NY, United States

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Published: 05 April 2020

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ICCMB 2020: 2020 The 3rd International Conference on Computers in Management and Business

January 31 - February 2, 2020

Tokyo, Japan

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Wang JMei HLi KZhang XChen X(2023)Collaborative Filtering Model of Graph Neural Network Based on Random WalkApplied Sciences10.3390/app1303178613:3(1786)Online publication date: 30-Jan-2023
https://doi.org/10.3390/app13031786
Mundargi ZMulay SNavale DTalnikar VNawale ASonkusale V(2023)An Aviation Industry Recommender System(AIRS) using K-nearest Neighbour and Cosine Similarity2023 International Conference for Advancement in Technology (ICONAT)10.1109/ICONAT57137.2023.10080009(1-6)Online publication date: 24-Jan-2023
https://doi.org/10.1109/ICONAT57137.2023.10080009

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Towards End-User Web Scraping for Customization

Effective web scraping with OXPath

Web Scraping versus Twitter API: A Comparison for a Credibility Analysis

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