skip to main content
ACM Transactions on Knowledge Discovery from Data
acm

The ACM Transactions on Knowledge Discovery from Data (TKDD) welcomes papers on a full range of research in the knowledge discovery and analysis of diverse forms of data. Such subjects include: scalable and effective algorithms for data mining and data warehousing, 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. 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.

Bibliometrics

Subject Areas

Announcements

Call for Nominations - Editor-in-Chief

As the term of the current Editor-in-Chief (EiC) of the ACM Transactions on Knowledge Discovery from Data  (TKDD) is coming to an end, the ACM Publications Board has set up a nominating committee to assist the Board in selecting the next EiC.

Nominations are now open for the three-year term of Editor-in-Chief (EiC) at TKDD, starting on January 1, 2024. The EiC term may be renewed once at most. Self-nominations are encouraged and should include a CV and a statement of the candidate's vision for the future development of TKDD.

The deadline for submitting nominations is Nov 30, 2023, although nominations will continue to be accepted until the position is filled. For the more information, please click here for the full announcement. 

ACM Updates Its Peer Review Policy

ACM is pleased to announce that its Publications Board has approved an updated Peer Review Policy. If you have any questions regarding the update, the associated FAQ addresses topics such as confidentiality, the use of large language models in the peer review process, conflicts of interest, and several other relevant concerns. If there are any issues that are not addressed in the FAQ, please contact ACM’s Director of Publications, Scott Delman.

New ACM Policy on Authorship

ACM has a new Policy on Authorship, covering a range of key topics, including the use of generative AI tools.  Please familiarize yourself with the new policy and the associated list of Frequently Asked Questions.

Most Frequent Affiliations

Most Cited Authors

Latest Issue

Most Popular