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Closer Look: Data Mining and Knowledge Discovery Journal


Data Mining and Knowledge Discovery Journal has a new EIC, has high impact factor, and allows researchers to publish open access.



By Gregory Piatetsky, @kdnuggets.

Back in 1997, I was one of the founding editors of the Data Mining and Knowledge Discovery Data Mining and Knowledge Discovery journal, the first journal in the field of data mining, along with Usama Fayyad and Raghu Ramakrishnan.

Lovers of history, can check my report on the First Issue of DMKD journal, 1997, or see the Wayback machine snapshot of the first issue.

The journal, now published by Springer, has come a long way since, and for many years was very ably edited by Geoff Webb.

Recently, a new editor-in-chief was appointed - Johannes Fuernkranz, a professor at TU Darmstadt and leading researcher in Inductive Rule Learning, Preference Learning, Web Mining, and Data Mining in Social Science.

Academic publishing is going through a difficult financial transition, and I look forward to how DMKD will navigate these difficult waters.

In the meantime, I wish all the success to Johannes and the journal!


Data Mining and Knowledge Discovery

Has Impact Factor: 1.743

  • The premier technical journal focused on the theory, techniques and practice for extracting information from large databases.
  • Publishes original technical papers in both the research and practice of data mining and knowledge discovery, surveys and tutorials of important areas and techniques, and detailed descriptions of significant applications.

 
Popular recent articles
  • Using the minimum description length to discover the intrinsic cardinality and dimensionality of time series - B. Hu et al
  • Survey on distance metric learning and dimensionality reduction in data mining - F. Wang, J. Sun
  • Learning a symbolic representation for multivariate time series classification - M. G. Baydogan, G. Runger

 
You can choose to publish your article open access.

Learn more at

link.springer.com/journal/10618


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