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, TangZhi-hang
- Quantitative Study of Commodity Review Text Based On Natural Language Processing.
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Authors
Affiliations
1 School of Computer and Communication, Hunan Institute of Engineering Xiangtan 411104., CN
2 School of Finance and Information, Ningbo University of Finance and EconomicsNingbo, 315300., CN
1 School of Computer and Communication, Hunan Institute of Engineering Xiangtan 411104., CN
2 School of Finance and Information, Ningbo University of Finance and EconomicsNingbo, 315300., CN
Source
International Journal of Advanced Networking and Applications, Vol 14, No 3 (2022), Pagination: 5482-5485Abstract
Choosing trusted reviews is the primary way that consumers get a true feelingabout buying products online. At present, many scholars study the authenticity and usefulness of shopping reviews, but itis difficult for us to effectively quantify review texts. This paper designs a quantitative method of commodityreviews based on Baidu natural language processing API interface. According to the technical means of Python Crawler, the reviewtext is extracted from the shoppingweb page, and the C-F model is established to analyze the review text quantitatively by calling the natural language processing technology of Baidu AI open platform. In this approach, the problems of natural language quantification and trust can be solved effectively.Keywords
Trust Review; Natural Language Processing; Baidu AI; Text quantization; C-F model.Full Text
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