ICDM: International Conference on Data Mining

FacebookTwitterLinkedInGoogle

 

Past:   Proceedings on DBLP

Future:  Post a CFP for 2018 or later   |   Invite the Organizers Email

 
 

All CFPs on WikiCFP

Event When Where Deadline
ICDM 2017 IEEE International Conference on Data Mining 2017
Nov 18, 2017 - Nov 21, 2017 NEW ORLEANS, USA Jun 5, 2017
ICDM 2016 The IEEE International Conference on Data Mining
Dec 12, 2016 - Dec 15, 2016 Barcelona, Spain Jun 17, 2016
ICDM 2015 International Conference on Data Mining
Nov 14, 2015 - Nov 17, 2015 Atlantic City, NJ, USA Jun 3, 2015
ICDM 2014 IEEE International Conference on Data Mining
Dec 14, 2014 - Dec 17, 2014 Shenzhen, China Jun 24, 2014
ICDM 2013 IEEE International Conference on Data Mining
Dec 8, 2013 - Dec 11, 2013 Dallas, Texas, USA Jun 21, 2013
ICDM 2012 IEEE International Conference on Data Mining
Dec 10, 2012 - Dec 13, 2012 Brussels / Belgium Jun 18, 2012
ICDM 2010 The 10th IEEE International Conference on Data Mining
Dec 13, 2010 - Dec 17, 2010 Sydney, Australia Jul 2, 2010
ICDM 2009 The 2009 IEEE International Conference on Data Mining
Dec 6, 2009 - Dec 9, 2009 Miami, FLorida ,USA Jun 26, 2009
ICDM 2008 The 8th IEEE International Conference on Data Mining
Dec 15, 2008 - Dec 19, 2008 Pisa, Italy Jul 7, 2008
 
 

Present CFP : 2017

The IEEE International Conference on Data Mining (ICDM) has established itself as the world’s premier research conference in data mining. It provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative and practical development experiences. The conference covers all aspects of data mining, including algorithms, software, systems, and applications. ICDM draws researchers, application developers, and practitioners from a wide range of data mining related areas such as statistics, machine learning, pattern recognition, databases, data warehousing, data visualization, knowledge-based systems, and high-performance computing. By promoting novel, high-quality research findings, and innovative solutions to challenging data mining problems, the conference seeks to advance the state-of-the-art in data mining.
Topics of Interest
Topics of interest include, but are not limited to:

Foundations, algorithms, models and theory of data mining, including big data mining.
Machine learning and statistical methods for data mining.
Mining from heterogeneous data sources, including text, semi-structured, spatio-temporal, streaming, graph, web, and multimedia data.
Data mining systems and platforms, and their efficiency, scalability, security and privacy.
Data mining for modeling, visualization, personalization, and recommendation.
Data mining for cyber-physical systems and complex, time-evolving networks.
Applications of data mining in social sciences, physical sciences, engineering, life sciences, web, marketing, finance, precision medicine, health informatics, and other domains.
We particularly encourage submissions in emerging topics of high importance such as data quality, time-evolving networks, big data mining and analytics, cyber-physical systems, and heterogeneous data integration and mining.

Submission Guidelines
Paper submissions should be limited to a maximum of ten (10) pages, in the IEEE 2-column format, including the bibliography and any possible appendices. Submissions longer than 10 pages will be rejected without review. All submissions will be triple-blind reviewed by the Program Committee on the basis of technical quality, relevance to scope of the conference, originality, significance, and clarity. The following sections give further information for authors.

Triple blind submission guidelines
Since 2011, ICDM has imposed a triple blind submission and review policy for all submissions. Authors must hence not use identifying information in the text of the paper and bibliographies must be referenced to preserve anonymity.

What is triple blind reviewing?
The traditional blind paper submission hides the referee name from the authors. The triple-blind paper submission and review, in addition, also hides the authors’ names from the referees, and the referees’ names during discussion. The names of authors and referees remain known only to the PC co-chairs, and the authors names are disclosed only after the ranking and acceptance of submissions are finalized. Although there is much debate on the merits and perceived benefits of triple blind reviewing, these are not discussed here. Our main purpose is to implement this policy in ICDM toward understanding the influence of the authors’ identity, whether conscious or unconscious, on the reviewer’s attitude toward a submission. Hence it is imperative that all authors of ICDM submissions work on concealing their identity in the content of the paper. It does not suffice to simply remove the authors’ names from the first page.

How to prepare your submissions
The authors shall omit their names from the submission. For formatting templates with author and institution information, simply replace all these information in the template by “Anonymous”.
In the submission, the authors’ should refer to their own prior work like the prior work of any other author, and include all relevant citations. This can be done either by referring to their prior work in the third person or referencing papers generically. For example, if your name is Smith and you have worked on clustering, instead of saying “We extend our earlier work on distance-based clustering (Smith 2005),” you might say “We extend Smith’s (Smith 2005) earlier work on distance-based clustering.”
The authors shall exclude citations to their own work which is not fundamental to understanding the paper, including prior versions (e.g., technical reports, unpublished internal documents) of the submitted paper. They should reference only necessary work using point (2). Hence, do not write: “In our previous work [3]” as it reveals that citation 3 is written by the current authors.
The authors shall remove mention of funding sources, personal acknowledgments, and other such auxiliary information that could be related to their identities. These can be reinstituted in the camera-ready copy once the paper is accepted for publication.
The authors shall make statements on well-known or unique systems that identify an author, as vague in respect to identifying the authors as possible.
The submitted files shall be named with care to ensure that authors’ anonymity is not compromised by the file name. For example, do not name your submission “Smith.pdf”, instead give it a name that is descriptive of the title of your paper, such as “ANewApproachtoClustering.pdf” (or a shorter version of the same).
Accepted papers will be published in the conference proceedings by the IEEE Computer Society Press.
All manuscripts are submitted as full papers and are reviewed based on their scientific merit. The reviewing process is confidential. There is no separate abstract submission step. There are no separate industrial, application, short paper or poster tracks. Manuscripts must be submitted electronically in online submission system. We do not accept email submissions.

Repeatability
Every effort should be made to enable the code and the datasets (or their closest publicly available equivalents) and all relevant parameter specifications available to reviewers and readers so that the results can be independently replicated. While we cannot expect *every* dataset used to be made public, it is in the best interest of the authors to make as many as possible available (in the worst case, a sampled or an anonymized version). To retain anonymity of submissions, any such additional material should be anonymized as well, and be published on an anonymous website (such as DropBox). The repeatability factor will play an important role in the reviewers’ assessment of the submission.

Best Paper Awards
Awards will be conferred at the conference on the authors of the best paper and the best student paper. A selected number of best papers will be invited for possible inclusion, in an expanded and revised form, in the Knowledge and Information Systems journal published by Springer.

Attendance
ICDM is a premier forum for presenting and discussing current research in data mining. Therefore, at least one author of each accepted paper must complete the conference registration and present the paper at the conference, in order for the paper to be included in the proceedings and conference program.

Important Dates
All deadlines are at 11:59PM Pacific Daylight Time.

Full paper submission: June 5, 2017
Author notification: August 15, 2017
Camera-ready submission: September 5, 2017
Conference: November 18-21, 2017
 

Related Resources

IEEE Big Data 2017   2017 IEEE International Conference on Big Data
ADAH 2017   Advanced Data Analytics in Health
ACML 2017   The 9th Asian Conference on Machine Learning
DSAA 2017   The 4th IEEE International Conference on Data Science and Advanced Analytics 2017
WSDM 2018   The 11th ACM International Conference on Web Search and Data Mining
ICDE 2018   IEEE International Conference on Data Engineering (ICDE)
ICCBDC - ACM 2017   International Conference on Cloud and Big Data Computing (ICCBDC 2017)--Ei Compendex and Scopus
SERecSys 2017   2nd ICDM Workshop on Semantics-Enabled Recommender Systems
MIWAI 2017   The 11th Multi-disciplinary International Workshop on Artificial Intelligence -- ISI CPCI, SCOPUS, EI Engineering index, DBLP
data-driven 2017   Special Issue on “Data-Driven User Behavioral Modeling: From Real-World Behavior to Knowledge, Algorithms, and Systems”