6th International Conference on Machine Learning and Data Mining

The Aim of the Conference

The aim of the conference is to bring together researchers from all over the world who deal with machine learning and data mining in order to discuss the recent status of the research and to direct further developments. Basic research papers as well as application papers are welcome.

All kinds of applications are welcome but special preference will be given to multimedia related applications, biomedical applications, and webmining. MLDM´2007 is the 6st event in a series of MLDM events that have been originally started out as a workshop. Paper submissions should be related but not limited to any of the following topics:

inductive learning including decision tree and rule induction learning
conceptional learning and clustering
case-based reasoning and learning
similarity measures and learning of similarity
association rules
visualization and data mining
video mining
mining structural representations such as log files, text documents and HTML documents
statistical learning and neural net based learning
classification and interpretation of images, text, video
organisational learning and evolutional learning
probabilistic information retrieval
mining gene data bases and biological data bases
mining images, temporal-spatial data, images from remote sensing
mining text documents
knowledge extraction from text, video, signals and images
Classification and Model Estimation
Decision Trees
Case-Based Reasoning and Associative Memory
Rule Induction and Grammars
Neural Methods
Nonlinear Function Learning and Neural Net Based Learning
Support Vector Machines
Bayesian Models and Methods
Subspace Methods
Statistical and Conceptual Clustering Methods: Basics
Applications of Clustering
Feature Grouping, Discretization, Selection and Transformation
Feature Learning
Learning/adaption of recognition and perception
Learning of internal representations and models
Learning of appropriate behaviour
Learning of action patterns
Learning in Image Pre-Processing and Segmentation
Statistical and Evolutionary Learning
Retrieval Methods
Content-Based Image Retrieval
Applications in Medicine
Time Series and Sequential Pattern Mining
Mining Financial or Stockmarket Data
Frequent Pattern Mining
Mining Images in Computer Vision
Mining Images and Texture
Mining Motion from Sequence
Real-Time Event Learning and Detection
Speech Analysis
Aspects of Data Mining
Text Mining
Symbolic Learning and Neural Networks in Document Processing
Deviation and Novelty Detection
Learning and adaptive control
Learning robots
Learning in process automation
Learning for Handwriting Recognition
Network Analysis and Intrusion Detection
Autoamtic Semantic Annotation of Media Content
Learning of Semantic Inferencing Rules
Learning of Ontologies
Learning of Visual Ontologies
High-Content Analysis of Microscopic Images in Medicine, Biotechnology and Chemistry

MLDM 2009

6th International Conference on Machine Learning and Data Mining

The Aim of the Conference