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