Big Data Mining and Analytics Impact Factor, Indexing, Ranking
Big Data Mining and Analytics (BDMA) is a scholarly journal dedicated to publishing research in the field of Computer Science. Institute of Electrical and Electronics Engineers is the publisher of this esteemed journal.
and its abbreviated form is Big Data Min Anal.
Big Data Mining and Analytics (Published by Tsinghua University Press) 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, CNKI, etc.
Abbreviation :ISO Journal abbreviation refers to the shortened form or acronym used to represent the full title of a scholarly journal. The ISO4 Abbreviation of Big Data Mining and Analytics Journal is Big Data Min Anal.
The Ranking of the Journal in 2024 is 859. Ranking systems aim to provide an indication of a journal's quality, influence, and prestige within a specific field or discipline.
The Journal's Impact Factor in 2024 is 13.6. it is all calculated by Clarivate, which means how many times a particular citation has been published in the past two years.
The Journal SCImago in 2024 is 2.533. It is measured by the number of citations which are made by the particular journals, and the journal from where the citations arrived from.
The Journal's H-Index in 2024 is 30. The H-index is calculated on how many times a particular author is cited and the number of published papers that a particular author has.
The Journal's Quartile is Q1. A quartile has three points, which are the upper quartile, median, and lower quartile. The main motive of the quartile is to calculate the interquartile range, that resembles the changes across the median.
Indexing services aim to make it easier for researchers, scholars, and readers to discover and access articles from various journals within a specific field or discipline.
Publishing in Big Data Mining and Analytics involves the following steps:
Research: Conduct high-quality, impactful research in the field of Computer Science.
Familiarize Yourself: Read and understand the aims and scope of Big Data Mining and Analytics to ensure your work aligns with their focus.
Manuscript Preparation: Prepare your manuscript according to the Big Data Mining and Analytics guidelines, including formatting, length, and referencing style.
Submission: Submit your manuscript through the journal's online submission system.