Big Data Mining and Analytics

Aims & Scope

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.

Metrics & Ranking

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Directory of Open Access Journals (DOAJ)

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, designed to support cutting-edge academic discovery.

Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

Policy Links

This section provides access to essential policy documents, guidelines, and resources related to the journal’s publication and submission processes.

• Aims scope
• Homepage
• Oa statement
• Author instructions
• License terms
• Review url
• Board url
• Copyright url
• Plagiarism url
• Apc url
• License

Plagiarism Policy

This journal follows a plagiarism policy. All submitted manuscripts are screened using reliable plagiarism detection software to ensure originality and academic integrity. Authors are responsible for proper citation and acknowledgment of all sources, and any form of plagiarism, including self-plagiarism, will not be tolerated.

For more details, please refer to our official: Plagiarism Policy.

APC Details

The journal’s Article Processing Charge (APC) policies support open access publishing in Computer Science, ensuring accessibility and quality in research dissemination.

This journal does not charge a mandatory Article Processing Charge (APC). However, optional open access publication may incur fees based on the publisher’s policies.

Explore journals without APCs for alternative publishing options.

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Multi-view clustering: A survey

  Citation: 397

  Authors: Yan, Hao

• Applications of deep learning to MRI images: A survey

  Citation: 236

  Authors: Jin, Yi, Min, Ziyue, Lu, Chengqian, Jianxin

• A survey of data partitioning and sampling methods to support big data analysis

  Citation: 212

  Authors: Mohammad Sultan, Joshua Zhexue, Salman, Tamer Z., Kuanishbay

• Big data with cloud computing: Discussions and challenges

  Citation: 211

  Authors: Amanpreet Kaur

• Security and Privacy in Metaverse: A Comprehensive Survey

  Citation: 197

  Authors: Yan, Yi Joy, Zhipeng

• IoT-based data logger for weather monitoring using arduino-based wireless sensor networks with remote graphical application and alerts

  Citation: 143

  Authors: Jamal, Mourade, Driss, Yousef, Souad El

• Big data analytics for healthcare industry: impact, applications, and tools

  Citation: 139

  Authors: Sunil, Maninder

• Prediction of COVID-19 confirmed, death, and cured cases in India using random forest model

  Citation: 131

  Authors: Vishan Kumar, Avdhesh, Dinesh, Anjali

• Improvising personalized travel recommendation system with recency effects

  Citation: 130

  Authors: Paromita, Joseph, Praveen

• Applying big data based deep learning system to intrusion detection

  Citation: 128

  Authors: Wei, Ning, Chunyu