Big Data Mining and Analytics Open Access Editors-in-Chief: Yi Pan, Weimin Zheng
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Overview

  • Big Data Mining and Analytics discovers hidden patterns, correlations, insights and knowledge through mining and analyzing large amounts of data obtained from various applications. It addresses the most innovative developments, research issues and solutions in big data research and their applications.

    Big Data Mining and Analytics is indexed and abstracted in ESCI, EI, Scopus, DBLP Computer Science, Google Scholar, INSPEC, CSCD, DOAJ and CNKI.

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  • Editors-in-Chief: Yi Pan, Weimin Zheng

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  • 7.7

    Impact Factor (2023)

  • 20.9

    CiteScore (2023)

Call for Papers

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Featured

ROBO-SPOT: Detecting Robocalls by Understanding User Engagement and Connectivity Graph
Muhammad Ajmal Azad, Junaid Arshad, Farhan Riaz
22 April 2024
E-Commerce Fraud Detection Based on Machine Learning Techniques: Systematic Literature Review
Abed Mutemi, Fernando Bacao
22 April 2024

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