Call For Papers

Call for Papers

PMML Workshop – 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-2013)
Sunday, August 11, 2013
Chicago Sheraton
301 East North Water Street (Link to map)
Chicago, IL


We invite submission of papers describing implementations of the Predictive Model Markup Language (PMML), including PMML deployment success stories, PMML in novel Environments/Cloud Computing, Privacy preservation in data mining, integration of PMML with other standards, PMML-based applications, PMML-based architectures, proposed extensions to the PMML standard, and related topics. The primary emphasis is on papers that advance the understanding of practical, applied, or pragmatic issues related to the use of PMML in KDD-related technologies in industry and government. Applications can be in any field including, but not limited to: e-commerce, medical and pharmaceutical, defense, public policy, engineering, manufacturing, telecommunications, and government.

Key D Dates:

  • Abstracts due: May 14, 2013, 23:59pm CT  Deadline extended to May 21st, 2013, 23:59pm CT
  • Papers due: May 24, 2013, 23:59pm CT  Deadline extended to May 31st, 2013, 23:59pm CT
  • Acceptance notification: June 1, 2013 June 5, 2013
  • Final Camera Ready Paper Due: June 7, 2013
  • Website:

Guidelines for Papers:

  • Submission and reviewing will be handled electronically.
  • All submissions must be in PDF format and must not exceed 10MB in size. Abstracts should be no more than 2000 characters.
  • Papers should be no more 9 pages total in length where up to 8 pages (including appendices, if any) are used for the content of the paper and the final page is used only for references. The format is the standard double-column ACM Proceedings Style. Additional information about formatting and style files are available online at: Papers that do not meet the formatting requirements will be rejected.
  • Abstracts and Papers should be emailed to:
  • Papers submitted to KDD 2013 should be original work and substantively different from papers that have been previously published or are under review in a journal or another peer-reviewed conference.

On behalf of the PMML Workshop Organizers:

• Robert Grossman, Open Data Partners and University of Chicago
• Michael Zeller, Zementis
• Svetlana Levitan, IBM