Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce

Submission Deadline: 31 October 2020 (closed)

Guest Editors

Prof. Honghao Gao, Shanghai University, China
Prof. Dr. Jung Yoon Kim, Gachon University, South Korea
Prof. Yuyu Yin, Hangzhou Dianzi University, China

Summary

In recent years, there is an increasing interest in new business models and strategies from both practitioners and researchers. The significant market transformation has been accomplished by leading E-commerce vendors such as Alibaba and Amazon through their innovative and highly scalable E-Commerce eco-systems. In the context of E-Commerce eco-system, there are hundreds of millions of consumers, thousands of businesses and shops, and hundreds of delivery people. Alibaba Group, as one of the main E-Commerce providers, cooperates with tens of thousands of software vendors to provide all necessary software services to support the business. With the booming of eco-business, more ecological roles in E-Commerce businesses emerge. For instance, Alibaba Group has expanded its business scale from Taobao Software to several business units, with 10000 plus technical staff. Large E-Commerce businesses such as Alibaba Group need to support a large number of applications and business modules, and cater for hundreds of business requirements and independent changes on a daily basis. Another new commercial mode, the sharing economy, such as Airbnb, Instacart, and Uber, has already operated on the basis of E-commerce eco-systems and information technologies. The intersection of these information technologies and business models provides ample research opportunities in intelligent processing of data, information and knowledge.

Keywords

• Best commercial practices and case studies in the field of E-commerce;
• Knowledge management for E-commerce;
• Date management for E-commerce;
• Literature review on emerging issues of new business models and strategies;
• New information technology for E-commerce, AI technology, Blockchain, Edge computing, service computing, etc;
• Business process management for E-commerce;
• Big data management and application in E-commerce;
• Demand analysis in E-commerce companies;
• Implementation risk and benefit of adopting digital technologies in E-commerce;
• Innovative mode in E-commerce;
• Consumer information sharing in E-commerce;
• The use of internet platform in E-commerce;
• Empirical studies of business practices and performance.

Published Papers

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EDITORIAL

Introduction to the Special Issue on “Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce”
Honghao Gao, Jung Yoon Kim, Yuyu Yin
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 19-21, 2022, DOI:10.32604/cmes.2022.019665
（This article belongs to this Special Issue: Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce)
Abstract This article has no abstract. More >

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ARTICLE

A Novel Named Entity Recognition Scheme for Steel E-Commerce Platforms Using a Lite BERT
Maojian Chen, Xiong Luo, Hailun Shen, Ziyang Huang, Qiaojuan Peng
CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 47-63, 2021, DOI:10.32604/cmes.2021.017491
（This article belongs to this Special Issue: Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce)
Abstract In the era of big data, E-commerce plays an increasingly important role, and steel E-commerce certainly occupies a positive position. However, it is very difficult to choose satisfactory steel raw materials from diverse steel commodities online on steel E-commerce platforms in the purchase of staffs. In order to improve the efficiency of purchasers searching for commodities on the steel E-commerce platforms, we propose a novel deep learning-based loss function for named entity recognition (NER). Considering the impacts of small sample and imbalanced data, in our NER scheme, the focal loss, the label smoothing, and the cross entropy are incorporated into… More >

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1306
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ARTICLE

A Knowledge-Enhanced Dialogue Model Based on Multi-Hop Information with Graph Attention
Zhongqin Bi, Shiyang Wang, Yan Chen, Yongbin Li, Jung Yoon Kim
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 403-426, 2021, DOI:10.32604/cmes.2021.016729
（This article belongs to this Special Issue: Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce)
Abstract With the continuous improvement of the e-commerce ecosystem and the rapid growth of e-commerce data, in the context of the e-commerce ecosystem, consumers ask hundreds of millions of questions every day. In order to improve the timeliness of customer service responses, many systems have begun to use customer service robots to respond to consumer questions, but the current customer service robots tend to respond to specific questions. For many questions that lack background knowledge, they can generate only responses that are biased towards generality and repetitiveness. To better promote the understanding of dialogue and generate more meaningful responses, this paper… More >

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ARTICLE

Number Entities Recognition in Multiple Rounds of Dialogue Systems
Shan Zhang, Bin Cao, Yueshen Xu, Jing Fan
CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 309-323, 2021, DOI:10.32604/cmes.2021.014802
（This article belongs to this Special Issue: Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce)
Abstract As a representative technique in natural language processing (NLP), named entity recognition is used in many tasks, such as dialogue systems, machine translation and information extraction. In dialogue systems, there is a common case for named entity recognition, where a lot of entities are composed of numbers, and are segmented to be located in different places. For example, in multiple rounds of dialogue systems, a phone number is likely to be divided into several parts, because the phone number is usually long and is emphasized. In this paper, the entity consisting of numbers is named as number entity. The discontinuous… More >

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1326
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ARTICLE

Dynamic Pricing Model of E-Commerce Platforms Based on Deep Reinforcement Learning
Chunli Yin, Jinglong Han
CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 291-307, 2021, DOI:10.32604/cmes.2021.014347
（This article belongs to this Special Issue: Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce)
Abstract With the continuous development of artificial intelligence technology, its application field has gradually expanded. To further apply the deep reinforcement learning technology to the field of dynamic pricing, we build an intelligent dynamic pricing system, introduce the reinforcement learning technology related to dynamic pricing, and introduce existing research on the number of suppliers (single supplier and multiple suppliers), environmental models, and selection algorithms. A two-period dynamic pricing game model is designed to assess the optimal pricing strategy for e-commerce platforms under two market conditions and two consumer participation conditions. The first step is to analyze the pricing strategies of e-commerce… More >

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1735
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ARTICLE

A User-Transformer Relation Identification Method Based on QPSO and Kernel Fuzzy Clustering
Yong Xiao, Xin Jin, Jingfeng Yang, Yanhua Shen, Quansheng Guan
CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1293-1313, 2021, DOI:10.32604/cmes.2021.012562
（This article belongs to this Special Issue: Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce)
Abstract User-transformer relations are significant to electric power marketing, power supply safety, and line loss calculations. To get accurate user-transformer relations, this paper proposes an identification method for user-transformer relations based on improved quantum particle swarm optimization (QPSO) and Fuzzy C-Means Clustering. The main idea is: as energy meters at different transformer areas exhibit different zero-crossing shift features, we classify the zero-crossing shift data from energy meters through Fuzzy C-Means Clustering and compare it with that at the transformer end to identify user-transformer relations. The proposed method contributes in three main ways. First, based on the fuzzy C-means clustering algorithm (FCM),… More >

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1361
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A Novel Collaborative Filtering Algorithm and Its Application for Recommendations in E-Commerce
Jie Zhang, Juan Yang, Li Wang, Yizhang Jiang, Pengjiang Qian, Yuan Liu
CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1275-1291, 2021, DOI:10.32604/cmes.2021.012112
（This article belongs to this Special Issue: Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce)
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 collaborative filtering algorithm by injecting… More >

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1473
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ARTICLE

E-Commerce Supply Chain Process Optimization Based on Whole-Process Sharing of Internet of Things Identification Technology
Shiyan Xu, Jun Chen, Maoguo Wu, Chenyang Zhao
CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.2, pp. 843-854, 2021, DOI:10.32604/cmes.2021.014265
（This article belongs to this Special Issue: Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce)
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 identification technology and the IoT… More >

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Cited by
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Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce

Guest Editors

Summary

Keywords

Published Papers

View

1464

Download

912

View

2060

Download

1306

View

2263

Download

1276

View

2074

Download

1326

View

2545

Download

1735

View

2113

Download

1361

View

2547

Download

1473

View

2935

Download

1932

Cited by

3

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