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Electronic Commerce Research
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Hybrid

Electronic Commerce Research - Call for Papers on Emerging Advances in Deep Learning and Computer Vision for Visual Data Search and Mining in E-commerce

Today, e-commerce is gaining momentum on a worldwide scale. Some of the most critical factors contributing to the growth of the e-commerce sector are the availability of multiple online platforms with a vast number of products, affordable prices, and ease of use for consumers. Thus, many businesses worldwide are now selling their products online through e-commerce websites. Computer vision techniques and deep learning have become valuable tools for visual search and mining within e-commerce. These new techniques use computer vision and deep learning to identify and classify objects in images and videos. Although deep-learning-based learning and computer vision for visual data search and mining in E-commerce is an emerging concept, the demand for visual data search and mining in E-commerce is rising significantly. Visual data search and mining in E-commerce have a significant role in improving the customer experience of utilizing e-commerce services. Deep learning and computer vision have opened a new vista in visual data search and mining in E-commerce. The dramatic advancement of deep learning and computer vision technologies provides a new possibility for building intelligent systems that can automatically perform the task of searching relevant images or items from massive visual data sets. This special issue provides a platform for researchers, students, engineers, and developers interested in applying deep learning and computer vision in E-commerce. Scope of the special issue include the following:

  • Visual data search and data mining in E-commerce with deep learning and computer vision
  • Real-time applications of deep learning and computer vision for E-commerce applications
  • Challenges and opportunities of deep learning big data analytics in E-commerce
  • Deep understanding assisted visual data mining for E-commerce
  • Efficient ways of customer trend prediction in E-commerce with deep knowledge and computer vision
  • Innovative use cases of deep expertise and computer vision in E-commerce
  • Personalized product recommendation in E-commerce application with deep learning and computer vision
  • Next digital frontier in E-commerce with deep learning and computer vision technologies
  • Computer vision applications in E-commerce with big data analytics
  • Visual data mining with deep learning for customized advertisement management and digital marketing in E-commerce
  • Enhancing sales and productivity in E-commerce with deep knowledge and computer vision
  • Visual data mining for user trend prediction and customer analysis


Guest Editors:
Dr. Hammam Alshazly
Assistant Professor, Department of Computer Science, Faculty of Computers and Information, South Valley University, Qena 83523, Egypt
Email: ha.alshazly@svu.edu.eg (this opens in a new tab), hammam.alshazly@gmail.com (this opens in a new tab)
ResearchGate: https://www.researchgate.net/profile/Hammam-Alshazly (this opens in a new tab)

Dr. Hela Elmannai
Associate Professor, Department of Information Technology, College of Computer and Information Science, Princess Nourah Bint Abdulrahman University, Riyadh, 11671, Saudi Arabia
Email: hselmannai@pnu.edu.sa (this opens in a new tab)
ResearchGate: https://www.researchgate.net/profile/Hela-Elmannai (this opens in a new tab)

Dr. Amir Benzaoui
Associate Professor, Electrical Engineering Department, University of Skikda, Skikda 21000, Algeria
Email: a.benzaoui@univ-skikda.dz (this opens in a new tab)
ResearchGate: https://www.researchgate.net/profile/Amir_Benzaoui (this opens in a new tab)

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