Proceedings of the 2022 3rd International Conference on Big Data and Informatization Education (ICBDIE 2022)

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Research on Big Data Analysis of Passenger-Oriented Railway Service Quality Based on LDA Model

Authors
Haohuan Yuan1, *, Hao Ding2, Pengcheng Lv3
1School of Mathematics, Hefei University of Technology, Hefei, Anhui, China
2School of Computer Science and Technology, Harbin Institute of Technology, Weihai, Shandong, China
3College of Shipbuilding Engineering, Harbin Engineering University, Harbin, Heilongjiang, China
*Corresponding author. Email: duoerxs@163.com
Corresponding Author
Haohuan Yuan
Available Online 23 December 2022.
DOI
10.2991/978-94-6463-034-3_132How to use a DOI?
Keywords
Latent Dirichlet Allocation; railway service quality; sentiment analysis; data mining
Abstract

Because of the lack of a reasonable evaluation and feedback system in China's railway transportation sector and the inability to make timely improvement according to the needs of passengers, this paper presents a passenger-oriented railway service quality big data analysis and research based on Latent Dirichlet Allocation (LDA) model. This method is of positive significance for railway departments to establish their evaluation and feedback system and opinion analysis. This paper excavates the needs of passengers in railway transportation and uses the Term Frequency-Inverse Document Frequency (TF-IDF) method to calculate text feature words and conducts semantic network analysis on them. Based on the above, the LDA topic model is used for modeling, and the best number of topics of comment data is determined by calculating the model confusion, and the LDA topic model is trained according to the best number of topics. Through the analysis of the model, the existing problems of railway traffic service based on the different demands of passengers are explored, and the emotional tendencies of current railway passengers are summarized based on the sentiment analysis algorithm.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 3rd International Conference on Big Data and Informatization Education (ICBDIE 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
23 December 2022
ISBN
10.2991/978-94-6463-034-3_132
ISSN
2589-4900
DOI
10.2991/978-94-6463-034-3_132How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Haohuan Yuan
AU  - Hao Ding
AU  - Pengcheng Lv
PY  - 2022
DA  - 2022/12/23
TI  - Research on Big Data Analysis of Passenger-Oriented Railway Service Quality Based on LDA Model
BT  - Proceedings of the 2022 3rd International Conference on Big Data and Informatization Education (ICBDIE 2022)
PB  - Atlantis Press
SP  - 1279
EP  - 1293
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-034-3_132
DO  - 10.2991/978-94-6463-034-3_132
ID  - Yuan2022
ER  -