Industrial Conference on Data Mining

20 июля23 июля 2020

Форма участия: Очная

Срок подачи заявок: 15.01.2020

Индексирование сборника: Springer

Организаторы: ICDM

emal: [email protected]

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This conference is the 20th conference in a series of industrial conferences on Data Mining that will be 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
  • Finance
  • Biology
  • Medicine
  • Marketing Medicine E-Commerce (Mining Logfiles)
  • Biotechnology
  • Quality Management
  • Multimedia Data (Image, Video, Text, Signals)
  • Web-Mining
  • Intrusion Detection in Networks
  • Agriculture
  • Meterology
  • Mining Social Media
  • Online Targeting & Controlling
  • Behavioral Targeting
  • Meteorological Data Mining
  • Data Mining in Logistics
  • Data Mining in Energy Industry
  • Business Intelligence and Data Mining
  • Big Data and Algorithm for Big Data
  • Legal Informatics and Data Mining
  • Data Mining for Logistic and Supply Chain Management

Theoretical and Application-oriented Topics in …

  • Case-Based Reasoning and Similarity-Based Reasoning
  • Clustering
  • Classification & Prediction
  • Statistical Learning
  • Association Rules
  • Telecommunication
  • Design of Experiment
  • Strategy of Experimentation
  • Capability Indices
  • 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

 

Authors can submit their paper in long or short version.

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