Big Data Mining and Analytics

metrics 2024

Shaping Tomorrow's Technologies with Big Data Insights

Introduction

Big Data Mining and Analytics, published by TSINGHUA UNIVERSITY PRESS, stands at the forefront of interdisciplinary research in the fields of Artificial Intelligence, Computer Networks and Communications, Computer Science Applications, and Information Systems. With an impressive Q1 ranking in multiple categories as of 2023, this journal serves as a critical platform for researchers and professionals eager to explore innovative techniques and methodologies related to big data analytics. Since its transition to Open Access in 2018, Big Data Mining and Analytics has aimed to increase the visibility and accessibility of its cutting-edge research, making permanent strides in the global academic landscape. Housed in Beijing, China, and actively embracing the converged years from 2018 to 2024, the journal aims to cultivate a rich discourse on emerging trends and applications, ensuring its relevance in a rapidly evolving technological environment. Join a vibrant community of scholars dedicated to advancing the frontiers of knowledge in big data.

Metrics 2024

SCIMAGO Journal Rank-
Journal Impact Factor7.70
Journal Impact Factor (5 years)6.60
H-Index-
Journal IF Without Self7.70
Eigen Factor0.00
Normal Eigen Factor0.31
Influence1.40
Immediacy Index1.90
Cited Half Life2.90
Citing Half Life5.50
JCI2.16
Total Documents-
WOS Total Citations875
SCIMAGO Total Citations-
SCIMAGO SELF Citations-
Scopus Journal Rank-
Cites / Document (2 Years)-
Cites / Document (3 Years)-
Cites / Document (4 Years)-

Metrics History

Rank 2024

IF (Web Of Science)

COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Rank 23/197
Percentile 88.60
Quartile Q1
COMPUTER SCIENCE, INFORMATION SYSTEMS
Rank 11/249
Percentile 95.80
Quartile Q1

JCI (Web Of Science)

COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Rank 16/198
Percentile 91.92
Quartile Q1
COMPUTER SCIENCE, INFORMATION SYSTEMS
Rank 15/251
Percentile 94.02
Quartile Q1

Quartile History

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