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Sai-feng, Zeng
- 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
References
- . Zeng Xiaoqin, Yu Hong. Sentiment analysis of commodity review text based on Python J. Computer Literacy and technology, 2020,1608:181-183.
- . Zhu Caiwei. The criminal law analysis of the behavior of letter-printing. Zhejiang Gongshang University, 2020.
- . The Gardener. The development and application of natural language processing technology in the era of artificial intelligence J. Office automation, 2019,2410:63-64.
- . GaoXin, Yang Ruyan, Guan Xiaofei, Wu Yong. A quantitative model of credibility for wine evaluation by WINE EXPERTS AND ITS APPLICATION J. Proceedings of the Yunnan Agricultural University, 2014,2902:235-240.
- . XuFangfang. Baidu brain: Born into the future. China Science and Technology Awards, 201811:50-53 + 82.
- . Wang Qiurong, Yu Zhihong. Take on the responsibility of AI for the benefit of mankind — A visit to vice president of Baidu Group, vice director of national engineering laboratory of deep learning technology and application, Wu Tianj. Journal of Sustainable Development Economics, 202004:21-23.
- . HaoErwei. Research on implementation technology of online translation software based on Baidu Cloud Service J. World of digital communications, 201912:106 + 7.
- . Shi Minghui, Zhou Changle, Wu Qingfeng, Wu Yun, Zhang Zhifeng. Uncertainty reasoning based on credibility and its neural network implementation of J. Computer Applications Research, 200701:241-243 + 312.
- . Chen Xiaoyu. Research and implementation of uncertainty inference engine based on Expert System J. Manufacturing automation, 2011,3318:78-81.
- . Zhang Yudong, Wu Le Nan, Wang Shuihua. Overview of Expert System Development J.Computer engineering and applications, 2010,4619:43-47.
- . Ni Jinling. A discourse strategy for product description in e-commerce platform environment — A case study of Amazon platform appliances. Journal of Lanzhou Institute of Education, 2019, 3506: 133-135.