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:

Applications of Data Mining in ...

    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