ACM Transactions on Knowledge Discovery from Data
Impact Factor Trend (2018–2026)
Clarivate IF trend for ACM Transactions on Knowledge Discovery from Data
SCImago Journal Rank citation prestige weighting
83 papers with at least that number of citations each
Aims & Scope
TKDD welcomes papers on a full range of research in the knowledge discovery and analysis of diverse forms of data. Such subjects include, but are not limited to: scalable and effective algorithms for data mining and big data analysis, mining brain networks, mining data streams, mining multi-media data, mining high-dimensional data, mining text, Web, and semi-structured data, mining spatial and temporal data, data mining for community generation, social network analysis, and graph structured data, security and privacy issues in data mining, visual, interactive and online data mining, pre-processing and post-processing for data mining, robust and scalable statistical methods, data mining languages, foundations of data mining, KDD framework and process, and novel applications and infrastructures exploiting data mining technology including massively parallel processing and cloud computing platforms. TKDD encourages papers that explore the above subjects in the context of large distributed networks of computers, parallel or multiprocessing computers, or new data devices. TKDD also encourages papers that describe emerging data mining applications that cannot be satisfied by the current data mining technology.
Special Issues
Calls for PapersNo active Calls for Papers found for this journal.
WoS Categories & Quartiles
Detailed JCR / JCI category rankings and quartile breakdown from Clarivate
COMPUTER SCIENCE, INFORMATION SYSTEMS
COMPUTER SCIENCE, SOFTWARE ENGINEERING
COMPUTER SCIENCE, INFORMATION SYSTEMS
COMPUTER SCIENCE, SOFTWARE ENGINEERING
Annual Historical Statistics & Publications
Track annual publication volume, total citations, and Impact Factor evolution
SCImago & Scopus Journal Intelligence
Global SCImago ranking, SJR prestige index, Scopus coverage, and societal policy impact
Weighted prestige citation metric per document indexed in the Scopus database.
Average citations received per document published in the 2-year window.
Estimated Article Processing Charge for Open Access publication.
Scopus 3-Year Publication & Citation Window
Aggregated from Scopus database across the 3-year SJR evaluation window.
Societal Impact & Inclusivity (SCImago)
Citations in government and international policy documents
Percentage of female authors published in the journal
Real-world societal policy reach and author gender diversity tracked by SCImago.
Scopus Subject Categories
Journal Metrics & Citation Visualizations
Total Cites vs Self-Cites
Evaluation of scholarly independence and citation reach
Citations per Document
Citation metric windows across 2, 3, and 4 years
Chinese Academy of Sciences (CAS) Classification
Major / minor zone classification and CAS Early Warning List history
Academic Intelligence Overview & Context
ImpaQ AnalysisACM Transactions on Knowledge Discovery from Data (acronym: tkdd, abbr: ACM TRANS. KNOWL. DISCOVERY DATA, ISSN: 1556-4681) is a peer-reviewed international scholarly journal in the field of COMPUTER SCIENCE, published by Association for Computing Machinery (ACM) in United States since 2006. The periodical holds a Journal Impact Factor (JIF) of 6.90, ranking in quartile Q1 of Web of Science (SCIE), a Scopus SJR indicator of 1.317 (Q1), an H-index of 83.
The journal enforces rigorous peer evaluation with an annual output of approximately 151 scientific articles. In terms of accessibility and author fees, it operates under the Hybrid model with an estimated APC of $3,508 USD. It serves as a benchmark publication platform for academics, researchers, and doctoral candidates seeking global research visibility.
Publishing & Editorial Information
Detailed publisher, peer-review turnaround, and publication cycle specifications
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