7th to 19th July 2018
New York, United States of America
Contact person: Prof. Dr. Petra Perner
The worldcongress DSA is comprised of three distinct conferences, three workshops, and four tutorials. Intern. Conf. on Machine Learning and Data Mining MLDM'2017 Industrial Conf. on Data Mining ICDM'2017 Intern. Conf. on Mass Data Analysis MDA
Organized by: Computer Vision and Applied Computer Sciences
Deadline for abstracts/proposals: 15th January 2018
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. Paper submissions should be related but not limited to any of the following topics:
association rules
Audio Mining
case-based reasoning and learning
classification and interpretation of images, text, video
conceptional learning and clustering
Goodness measures and evaluaion (e.g. false discovery rates)
inductive learning including decision tree and rule induction learning
knowledge extraction from text, video, signals and images
mining gene data bases and biological data bases
mining images, temporal-spatial data, images from remote sensing
mining structural representations such as log files, text documents and HTML documents
mining text documents
organisational learning and evolutional learning
probabilistic information retrieval
Selection bias
Sampling methods
Selection with small samples
similarity measures and learning of similarity
statistical learning and neural net based learning
video mining
visualization and data mining
Applications of Clustering
Aspects of Data Mining
Applications in Medicine
Autoamtic Semantic Annotation of Media Content
Bayesian Models and Methods
Case-Based Reasoning and Associative Memory
Classification and Model Estimation
Content-Based Image Retrieval
Decision Trees
Deviation and Novelty Detection
Feature Grouping, Discretization, Selection and Transformation
Feature Learning
Frequent Pattern Mining
High-Content Analysis of Microscopic Images in Medicine, Biotechnology and Chemistry
Learning and adaptive control
Learning/adaption of recognition and perception
Learning for Handwriting Recognition
Learning in Image Pre-Processing and Segmentation
Learning in process automation
Learning of internal representations and models
Learning of appropriate behaviour
Learning of action patterns
Learning of Ontologies
Learning of Semantic Inferencing Rules
Learning of Visual Ontologies
Learning robots
Mining Financial or Stockmarket Data
Mining Images in Computer Vision
Mining Images and Texture
Mining Motion from Sequence
Neural Methods
Network Analysis and Intrusion Detection
Nonlinear Function Learning and Neural Net Based Learning
Real-Time Event Learning and Detection
Retrieval Methods
Rule Induction and Grammars
Speech Analysis
Statistical and Conceptual Clustering Methods: Basics
Statistical and Evolutionary Learning
Subspace Methods
Support Vector Machines
Symbolic Learning and Neural Networks in Document Processing
Text Mining
Time Series and Sequential Pattern Mining
Mining Social Media Extended Paper Submission Deadline: February 16, 2018
Notification of acceptance: 18.03.2018
Submission of camera-ready copy: 05.04.2018