Call for Papers - Special Issue on Artificial Intelligence for Data Models and Communication-Aware Data Management Solutions in E-Business Applications

2022-10-07

In today's economy, staying competitive and managing business expenses is crucial. Data models are the blueprints of business data. They describe the structure and relationships of information. E-business applications are becoming increasingly critical as they represent the key to flexibility, extensibility, and data integrity in an ever-changing environment. The importance of artificial intelligence (AI) in e-business applications has been increasing in recent years. With the advancement of generations of AI, e-business application companies are expected to utilize ontology, a specific form of AI, to implement services that may be supported through online environments. Implementation of the cutting edge data models and intelligent systems in e-business applications will streamline the processes significantly and provide a competitive advantage.

Artificial intelligence technologies and data modeling techniques can effectively be integrated to significantly enhance the development of meaningful e-business applications. AI-assisted communication-aware data management solutions technology automates complex repetitive tasks requiring accurate decision-making and handling many concurrent tasks and objectives. It is helpful in communications-aware applications where collaboration between humans and automated systems is necessary to achieve desired results, such as fraud detection, spam filtering, document management, etc. In the current situation, Data models in e-business applications must cope with human and computer interpretations of data. Standard data models fail to capture semantics of data that are ambiguous to both humans and computers. This scenario leads to incompatible data representations in different applications and high maintenance costs. We require formalisms that can be used to describe complex data models in such a way that their meaning is clear to humans and their structure is unambiguous to machines. Although AI-assisted data models provide several opportunities, some challenges remain unaddressed. The main difficulties of AI-assisted data models for e-business applications are development challenges, integration with current infrastructure challenges and security challenges. Moreover, Data mining algorithms are critical components of many business applications, including recommendation engines, fraud detection systems, and communication systems for e-commerce sites. However, the effectiveness of these algorithms depends on how well their training data reflect real-world problems that arise in running e-business applications. This requires AI-assisted data models to represent data from real-world applications accurately and to be able to incorporate context-specific knowledge into predictive models. Currently, AI technology is used in a variety of data modeling and data presentation scenarios including discovery analytics, visualization, user profiling and human-machine collaborative application development. In such models, however, poor run time performance often restricts their usage to the laboratory environment.

This special issue investigates potential challenges and opportunities for AI-assisted data modelling. Focusing on the principles and ideas that drive its successful application, we expect a vast number of case studies, researches and manuscripts illustrating how AI-assisted data models can be used to solve real-world business applications.

Topics of Interest:

  • Role of intelligent autonomous systems in e-business applications
  • Influence of big data models in managing communications in e-business
  • AI for perception and awareness in e-businesses
  • Real-time data analytics and AI practices in e-commerce applications
  • New frontiers in Multimodal data integration and semantic data models in e-businesses
  • Big data modelling and mining involving communication-aware data management solutions in E-Business Applications
  • AI-driven traffic estimation and prediction system in e-business applications
  • Frontiers in high-performance network virtualization for e-commerce
  • AI-assisted innovative mobility management solutions for data of e-business applications
  • AI-driven data security and privacy in communication networks for e-commerce applications
  • Emerging trends in e-commerce security protocols foe existing data management solutions
  • Future prospects for intelligent resource utilization for e-business applications

 

Important Timeline
Submission deadline: January 12, 2023
Final notification: August 28, 2023

Guest Editors
B. Santhosh Kumar (Managing Guest Editor), Guru Nanak Institute of Technology, Hyderabad, Telangana, India
BalaAnand Muthu, Adhiyamaan College of Engineering, India
Imran Shafique Ansari, University of Glasgow, United Kingdom