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ICDM 2023

20h Industrial Conference on Data Mining ICDM 2023

New York, United States
12 - 16 July 2023
The conference ended on 16 July 2023

Important Dates

Abstract Submission Deadline
15th January 2023
Abstract Acceptance Notification
15th January 2023
Early Bird Deadline
1st March 2023
Final Abstract / Full Paper Deadline
20th April 2023

About ICDM 2023

The Industrial Conference on Data Mining ICDM is held on yearly basis. Researchers from all over the world will present theoretical and application-oriented topics on Data Mining. Practicioners can present and discuss their ongoing projects in Industry Sessions.

Topics

Data mining and cloud computing, Intelligent data mining, Applications of data mining, Ehealth & big data, Big data in railway, Data mining and machine learning tools, Big data management and analytics, Data mining in pattern recognition, Bio-ontology and data mining genes and their regulation, Data mining in food and agriculture, Big data for mobile and iot, Big data methods in economics and social sciences, Internet and big data applications, Big data and intelligent information processing, Big data

Call for Papers

Call for Papers ICDM 2023

Chair 

Petra Perner   Institute of Computer Vision and applied Computer Sciences IBaI, Germany

The Aim of the Conference

The Industrial conferences on Data Mining ICDM is held on yearly basis. Experts from different fields will present their applications and the results obtained by applying data mining. Besides that, newcomers in the field can get a fast introduction to Data Mining by taking the tutorial running in connection with the conference. In a problem/solution hour you will have the opportunity to present your application and ask for support by others or for cooperation in solving the problem.

Topics of the conference

Paper submissions should be related but not limited to any of the following topics:

  • Marketing
  • Medicine
  • Civil Engineering
  • E-Commerce (Mining Logfiles)
  • Biotechnology
  • Quality Management
  • Multimedia Data (Image, Video, Text, Signals)
  • Web-Mining
  • Intrusion Detection in Networks
  • Criminology
  • Telecommunications
  • Social Sciences
  • Forensic Data Analysis
  • Drug Discovery
  • Agriculture
  • Smart Maintenance
  • Legal Court Cases
  • Energy Industries
  • Logistics and Supply Chain Management
  • Finance and Stock Markets
  • Meterology, Blockchain and more ...

     

    Theoretical and Application-oriented Topics in ...

    • Big Data and Algorithm for Big Data
    • Case-Based Reasoning and Similarity-Based Reasoning
    • Clustering
    • Classification & Prediction
    • Statistical Learning
    • Association Rules
    • Deviation and Novelty Detection
    • Control Charts
    • Conceptional Learning
    • Goodness Measures and Evaluation (e.g. false discovery rates)
    • Inductive Learning Including Decision Tree and Rule Induction Learning
    • Organisational Learning and Evolutional Learning
    • Sampling Methods
    • Similarity Measures and Learning of Similarity
    • Statistical Learning and Neural Net Based Learning
    • Visualization and Data Mining
    • Deviation and Novelty Detection
    • Feature Grouping, Discretization, Selection and Transformation
    • Feature Learning
    • Frequent Pattern Mining
    • Learning and Adaptive Control
    • Learning/Adaption of Recognition and Perception
    • Learning for Handwriting Recognition
    • Learning in Image Pre-Processing and Segmentation
    • Mining Financial or Stockmarket Data
    • Mining Motion from Sequence
    • Subspace Methods
    • Support Vector Machines
    • Time Series and Sequential Pattern Mining
    • Desirabilities
    • Graph Mining
    • Agent Data Mining
    • Applications in Software Testing
    • Knowledge Management
    • Mining Social Media
    • Online Targeting & Controlling
    • Behavioral Targeting
    • Meteorological Data Mining
    • Data Mining in Energy Industry
    • Design of Experiment
    • Strategy of Experimentation
    • Capability Indices
    • Business Intelligence and Data Mining
    • Legal Informatics and Data Mining
    • Data Mining for Logistic and Supply Chain Management

     

    Authors can submit their paper in long or short version.

    Long Paper

    The paper must be formatted in the Springer LNCS format. They should have at most 15 pages. The papers will be reviewed by the program committee. Papers will appear in the conference proceedings.

    Please submit your Long Paper to easychair https://easychair.org/ CMS-System.

    Short Paper

    Short papers are also welcome and can be used to describe work in progress or project ideas. They can have 5 to max. 15 pages, formatted in Springer LNCS format. Accepted short papers will be presented as poster in the poster session. They will be published in a special poster proceedings book.

    Please submit your Short Paper and your Industry Paper to the CMS-System.

    Industry Papers

    We encourage industrial people to show their applications and projects for data mining. This work can be presented as poster during the poster session in the special industry track. Please submit a one page abstract including title, name and affilation.

    Please submit your Short Paper and your Industry Paper to the CMS-System.

    Notice that the submission is NOT the registration to the conference! Please fill out the registration form.

    If you have any problem with the submission, please contact via email info@data-mining-forum.de.

    Important Dates

Deadline Long Paper

  • Submission deadline January 15th, 2023
  • Notification of acceptance: 20.03.2023
  • Submission of camera-ready copy: 20.04.2023
  • Please submit the electronic version of your long paper to the CMS-System

 

Deadline Short Paper and Industry paper

  • Submission of papers: 20.03.2023
  • Notification of acceptance: 29.04.2023
  • Submission of camera-ready copy: 10.05.2023
  • Please submit your Short Paper and your Industry Paper to the CMS-System.

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