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Issue title: Special issue: Fuzzy Systems in Distributed Sensing Applications
Guest editors: Mohamed Elhoseny and X. Yuan
Article type: Research Article
Authors: Zhou, Qingyuana | Zhang, Zongmingb; c | Wang, Yuancongd; *
Affiliations: [a] School of Economics and Management, Changzhou Vocational Institute of Mechatronic Technology, China | [b] School of Economics and Management, Xidian University, Xi’an, China | [c] Naveen Jindal School of Management, The University of Texas at Dallas, Richardson, TX, USA | [d] School of Public Administration, Sichuan University, Chengdu, China
Correspondence: [*] Corresponding author. Yuancong Wang, School of Public Administration, Sichuan University, Chengdu 610065, China. Tel.: +86 182 0818 7552; E-mail: [email protected].
Abstract: With the rapid popularization and rapid development of the Internet in the world, e-commerce has gradually become the mainstream trade mode. E-commerce has its own unique trading mode and brand-new global business opportunities. More and more people conduct online transactions through the Internet. According to the characteristics of data in B2C e-commerce system, data mining management module is designed in B2C e-commerce management system. Data mining technology is used to preprocess data, data mining and mining results. It is implemented using J2EE’s B/S architecture. With the continuous growth of B2C e-commerce scale, logistics bottlenecks have become increasingly prominent, and e-commerce distribution model based on cloud logistics integrates IT information technology with traditional logistics information systems. Integrate logistics service demand and logistics distribution capabilities, and provide corresponding cloud logistics information and management platform system. It will help solve the problem of logistics and distribution of B2C e-commerce in China and promote the healthy and rapid development of e-commerce economy.
Keywords: Data Cube, B2C E-Commerce, Intelligent Logistics
DOI: 10.3233/JIFS-179522
Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 2, pp. 1585-1592, 2020
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