Text Analysis of Commodity Evaluation Data Mining Based on LDA Theme Model

DOI

10.2991/978-94-6463-224-8_39How to use a DOI?

Keywords

Commodity evaluation; LDA model; Data mining; Consumer preference

Abstract

With the development of e-commerce industry, product reviews have become an important bridge between consumers and businesses. Consumers intuitively express their opinions and comments on products or services through product reviews, making online reviews an important basis for online businesses to improve service quality. In order to improve the service quality of online merchants, this paper uses Python’s crawler technology to crawl 1000 favorable comments, 1000 moderate comments and 1000 bad comments of JD.COM Midea Heater, and mines and analyzes online comments, and uses LDA (Latent Dirichlet Allocation) model to process online comment data, so as to find out consumers’ concerns about goods, thus providing merchants with ideas for improving services from comments.

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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TY  - CONF
AU  - Qian Zhang
PY  - 2023
DA  - 2023/08/23
TI  - Text Analysis of Commodity Evaluation Data Mining Based on LDA Theme Model
BT  - Proceedings of the 2023 3rd International Conference on Enterprise Management and Economic Development (ICEMED 2023)
PB  - Atlantis Press
SP  - 316
EP  - 320
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-224-8_39
DO  - 10.2991/978-94-6463-224-8_39
ID  - Zhang2023
ER  -