Haoliang Cui¹, Shaozhang Niu¹, Keyue Li^1,*, Chengjie Shi², Shuai Shao³, Zhenguang Gao⁴

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 277-291, 2021, DOI:10.32604/iasc.2021.016408 - 17 March 2021

Abstract At present, the research on the classification of e-commerce users is relatively mature, but with the rise of mobile social networks, the combination of social networks and e-commerce networks has become a trend and is developing rapidly. Traditional e-commerce user classification methods are not suitable for social e-commerce users. Therefore, based on the research on traditional e-commerce user classification methods, according to the characteristics of social e-commerce users, we improved data preprocessing and parameter tuning methods, and proposed a clustering method of social e-commerce users based on the K-means++ algorithm. The test on the actual More >

Jie Zhang^1,5, Juan Yang^2,*, Li Wang³, Yizhang Jiang⁴, Pengjiang Qian⁴, Yuan Liu⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1275-1291, 2021, DOI:10.32604/cmes.2021.012112 - 19 February 2021

Abstract With the rapid development of the Internet, the amount of data recorded on the Internet has increased dramatically. It is becoming more and more urgent to effectively obtain the specific information we need from the vast ocean of data. In this study, we propose a novel collaborative filtering algorithm for generating recommendations in e-commerce. This study has two main innovations. First, we propose a mechanism that embeds temporal behavior information to find a neighbor set in which each neighbor has a very significant impact on the current user or item. Second, we propose a novel More >

Shiyan Xu¹, Jun Chen^2,*, Maoguo Wu², Chenyang Zhao²

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.2, pp. 843-854, 2021, DOI:10.32604/cmes.2021.014265 - 21 January 2021

Abstract With in-depth development of the Internet of Things (IoT) in various industries, the informatization process of various industries has also entered the fast lane. This article aims to solve the supply chain process problem in e-commerce, focusing on the specific application of Internet of Things technology in e-commerce. Warehousing logistics is an important link in today’s e-commerce transactions. This article proposes a distributed analysis method for RFID-based e-commerce warehousing process optimization and an e-commerce supply chain management process based on Internet of Things technology. This article first introduces the advantages and disadvantages of shared IoT… More >

Malik Javed Akhtar¹, Zahur Ahmad¹, Rashid Amin^{1, *}, Sultan H. Almotiri², Mohammed A. Al Ghamdi², Hamza Aldabbas³

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2639-2663, 2020, DOI:10.32604/cmc.2020.011485 - 16 September 2020

Abstract A large amount of data is present on the web which can be used for useful purposes like a product recommendation, price comparison and demand forecasting for a particular product. Websites are designed for human understanding and not for machines. Therefore, to make data machine-readable, it requires techniques to grab data from web pages. Researchers have addressed the problem using two approaches, i.e., knowledge engineering and machine learning. State of the art knowledge engineering approaches use the structure of documents, visual cues, clustering of attributes of data records and text processing techniques to identify data… More >

Bing Xu^1,∗, Darong Huang^2,†, Bo Mi^3,‡

Computer Systems Science and Engineering, Vol.35, No.2, pp. 113-121, 2020, DOI:10.32604/csse.2020.35.113

Abstract In this paper, according to the information classification algorithm in data mining, data in the network payment system of e-commerce is mined, forming an effective evaluation of the security of the network payment system. Firstly, the method of network security risk prediction is discussed. Secondly, according to the characteristics of network payment system, the system security index system is analyzed in detail, and the specific application process of the C4.5 Classification Algorithm in security evaluation is discussed. Finally, the data mining process is designed in detail and the corresponding code established. In this paper, data More >

Shuangying Liu¹, Weidong Zhang^2,*

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 569-575, 2020, DOI:10.32604/iasc.2020.013935

Abstract The constant development of computer technology has greatly facilitated our life. In the past, the agricultural products trade and agricultural products business model were an offline development, through face-to-face transactions. However, with the continuous application of Internet technology, we also have a new exploration on the e-commerce path of agricultural products. The fuzzy neural network algorithm was used to study the electronic commerce path of agricultural products and helped us to carry out the exploration computation of the electronic commerce path of agricultural products. And good calculation results have been obtained. Through our testing of More >

Hangjun Zhou^1,2,*, Guang Sun^1,3, Sha Fu¹, Wangdong Jiang¹, Juan Xue¹

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 179-192, 2019, DOI:10.32604/cmc.2019.05214

Abstract With the rapid development of mobile Internet and finance technology, online e-commerce transactions have been increasing and expanding very fast, which globally brings a lot of convenience and availability to our life, but meanwhile, chances of committing frauds also come in all shapes and sizes. Moreover, fraud detection in online e-commerce transactions is not totally the same to that in the existing areas due to the massive amounts of data generated in e-commerce, which makes the fraudulent transactions more covertly scattered with genuine transactions than before. In this article, a novel scalable and comprehensive approach More >