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Big Data fusion and Intelligent Information Integration

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Editorial Board
Lead Guest Editors:
  • Asif Ali Laghari (Sindh Madressatul Islam University)
  • Shoulin Yin (HIT)+ BioDr in HIT, China
Guest Editors:
  • liu zhiguo (Dalian University)
Aims & Scope

Intelligent information integration has continued to challenge research for over 30 years. While data fusion processes are now well understood and widely used, a great deal of interest in Big Data Fusion requires much higher levels of automation to limit the need for skilled human labor. In recent years, much of the big data work has focused on volume and speed to consider the size of the data set. Indeed, the problems of variety, speed, and truthfulness are equally important in addressing the heterogeneity, diversity, and complexity of data in the big data fusion process, where intelligent information integration and semantic technologies can be explored to address these problems.


  • Automating data cleaning and pre-processing for big data;
  • Intelligent information integration from big data on the P2P systems;
  • Data quality issues in big data fusion;
  • Scalability issues: intelligent information integration for big data;
  • Metadata integration and management;
  • Entity resolution and data fusion for big data;
  • AI approaches for Big Data Fusion;
  • Image processing based on Intelligent Information Integration;
  • QoS/QoE for Big Data;
  • Semantic for big data extraction, transformation, and integration.
Manuscript submission deadline:
Notification of acceptance:
Submission of final revised paper:
Publication date (tentative):