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CFP: The 16th INFORMS Workshop on Data Mining and Decision Analytics (Papers Due Aug. 2)

  • 1.  CFP: The 16th INFORMS Workshop on Data Mining and Decision Analytics (Papers Due Aug. 2)

    Posted 07-18-2021 23:44
    CALL FOR PAPERS
    The 16th INFORMS Workshop on Data Mining and Decision Analytics
    October 23, 2021, Anaheim, CA
    Organized by INFORMS Data Mining (DM) Section

     

    The Data Mining Section of INFORMS is organizing the 16th INFORMS Workshop on Data Mining and Decision Analytics in conjunction with 2021 INFORMS Annual Meeting. You are cordially invited to join us and share your recent research work with peers from data mining, decision analytics, and artificial intelligence.

    To participate, a full paper must be submitted before the deadline for consideration. The workshop committee also announces the best paper competition in both theoretical and applied research tracks. All accepted papers are automatically considered for the best paper competition in the chosen track. Suitable best papers and runner-ups will be recommended for fast-track submission to INFORMS Journal on Data Science (IJDS).

    Papers accepted for presentation at the workshop will also be encouraged for submission to the Data Science and Decision Analytics Special Issue in Annals of Operations Research. More information can be found at this link.

     

    Topics of interest include, but are not limited to:

    • Large-Scale Data Analytics and Big Data
    • Data-Driven Decision-Making
    • Interpretable Data Mining
    • Simulation/Optimization in Data Analytics
    • Network Analysis and Graph Mining
    • Privacy & Fairness in Data Science
    • Bayesian Data Analytics
    • Healthcare Analytics
    • Longitudinal Data Analysis
    • Causal Mining (Inference)
    • Anomaly Detection
    • Deep Learning
    • Reinforcement Learning
    • Emerging Data Analytics in Industrial Applications
    • Analytics in Social Media & Finance
    • Reliability & Maintenance
    • Visual Analytics
    • Web Analytics/Web Mining
    • Text Mining & Natural Language Processing
    • Ethics and Security in Data Mining
    • Fairness in Machine Learning

    Timeline

    • May 1: Paper submission begin            
    • August 2: Paper submission close
    • September 1:  Final review decision
    • September 14: Workshop on Data Mining and Decision Analytics registration deadline

    Papers submission guideline

    • Maximum of 10 pages (including abstract, tables, figures, and references)
    • Do not use your name or your co-authors' names, affiliations, funding sources, or acknowledgments in the heading or body of the document. Submissions will go through a double-blind review. 
    • Single-spacing and 11-point font with one-inch margins on four sides
    • Papers must be submitted via this link. Late submission will not be considered for further review.
    • Copyright: The DM workshop will not retain the copyrights on the papers; so, the authors are free to submit their papers to other outlets, unless they want the paper to be considered for fast-track submission to INFORMS Journal on Data Science (IJDS).
    • Fast-track submission to IJDS: The IJDS publishes innovative and impactful data science methodologies contributing to decision-making in business, management, and industry. To increase chances to be considered for fast-track submission, a paper should include novel methodology or existing methodology applied in a completely new way ("methodological discovery").

    DM Workshop Co-Chairs

    • Eyyub Kibis, Montclair State University
    • Chen Kan, University of Texas at Arlington 
    • Nathan Gaw, Georgia Institute of Technology

    DM Workshop Management Committee 

    • George Runger, Arizona State University
    • Cynthia Rudin, Duke University
    • Paul Brooks, Virginia Commonwealth University
    • Onur Seref, Virginia Tech
    • Asil Oztekin, University of Massachusetts Lowell
    • Matthew Lanham, Purdue University
    • Ramin Moghaddass, University of Miami
    • Durai Sundaramoorthi, Washington University

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    Data Mining Section Workshop Committee
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    Eyyub Kibis
    Assistant Professor of Business Analytics
    Montclair State University
    Montclair NJ
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