International Journal of Advanced Networking and Applications

Open Access Open Access  Restricted Access Subscription Access

Quantitative Study of Commodity Review Text Based On Natural Language Processing.


Affiliations
1 School of Computer and Communication, Hunan Institute of Engineering Xiangtan 411104., China
2 School of Finance and Information, Ningbo University of Finance and EconomicsNingbo, 315300., China
 

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.
User
Notifications
Font Size

  • . 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.


Abstract Views: 98

PDF Views: 0




  • Quantitative Study of Commodity Review Text Based On Natural Language Processing.

Abstract Views: 98  |  PDF Views: 0

Authors

Zhou Zi-kai
School of Computer and Communication, Hunan Institute of Engineering Xiangtan 411104., China
TangZi-pei
School of Finance and Information, Ningbo University of Finance and EconomicsNingbo, 315300., China
Zeng Sai-feng
School of Computer and Communication, Hunan Institute of Engineering Xiangtan 411104., China
TangZhi-hang
School of Computer and Communication, Hunan Institute of Engineering Xiangtan 411104., China

Abstract


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.

References