Word of the Chair and Mission of the Congress


Dear Colleagues and Participants,

It gives us great pleasure to invite you to the third World Congress "The Frontier of Intelligent Data and Signal Analysis" DSA 2013 in New York. This is one of the most important international conferences in the field of Data Mining and Machine Learning, where you can learn about the latest developments and trends. The congress combines top-notch scientific events with specialized industrial forums and exhibitions, thus offering an excellent platform for scientists, engineers and decision makers from industry, but also for young professionals, for acquiring thorough, quick and broad information on this subject.

Why is intelligent data and signal analysis of such importance?

Our everyday life nowadays is characterized by the digital age. Every day a multitude of information is created that can be processed by computers. This information often exists as data base entries in numerical or symbolic form. There are, however, digital signals also that are collected and stored for example by medical equipment in diagnosis and the surveillance of patients, but also in industrial production and quality control.

In the World Wide Web users of web contents and also the providers leave a large number of data that can be used for further analysis. A multitude of image data is stored that is created by many individuals with digital cameras for personal use, but also in the professional field by scanners in medicine or industry. In addition, there are texts in digital form that are published in the internet by professionals or private persons.

All this data forms a data pool that should do more than just fill the servers or databases of the world and thus strain resources. To create from this data flood a new quality that leads to new products, treatments in medicine, new services - this should be the way into a new future, always geared to the needs of the human being. It requires intelligent mathematical procedures that can be translated into computer programs and that can efficiently convert this enormous data flood into information of general interest.

Why participate, and in which way, in the World Congress "The Frontier of Intelligent Data and Signal Analysis" DSA?

The World Congress "The Frontier of Intelligent Data and Signal Analysis" DSA is the most important international congress dedicated to this subject. It presents the essential new methods from the fields of Data Mining and Machine Learning in general, but also from the specialties Web Mining, Image Mining, Text Mining, Multimedia Data Mining, Time Series Mining etc..

The World Congress "The Frontier of Intelligent Data and Signal Analysis" DSA combines three international conferences:

When you are working in one of these topics, we like to encourage you to choose one of these conferences for your presentation. Figure 1 should give you an overview where to present your work.

Figure 1: Topics of Intelligent Data
						and Signal Analysis versus MLDM, ICDM, and MDA conferences
Figure 1: Topics of Intelligent Data and Signal Analysis versus MLDM, ICDM, and MDA conferences


In the past few years the following topics have developed at the international conferences that this congress unites. They have led to new and innovative ideas that industry formed into new products.

Figure 2.
Figure 2.


The applications that are presented at this congress comprise a wide field of marketing applications, medical and LifeScience applications, industrial applications and also agricultural applications (see at the bottom of this message for more information). Once more the diverse application possibilities of intelligent signal-analysis methods are pointed out.

The World Congress thus responds to all aspects of novel data analysis. Leading scientists from research and industry present their work and discuss novel ideas with you. Do make use of the opportunity to inform yourself about the new data-analysis methods. Meet the key players in the field and create networks, so that efficient and intelligent new problems can be tackled.

The World Congress is also a platform for companies, decision makers from industry and marketing, and for networking!

Next to the scientific program, interested companies and representatives from industry have the possibility to present their projects on intelligent data and signal analysis and discuss them with leading experts from industry and research.

Use the opportunity to present your projects and your company on the renowned international World Congress in New York to a highly qualified expert public. Make the acquaintance of leading experts from the field of Data Mining and form a network for future projects and latest developments.

Job fair

Get to know experts and young professionals from research who are interested in industrial developments and would like to increase their qualified staff.

Industrial Exhibition

There is also the possibility of participating in the Industrial Exhibition, where you can present your data mining and data analysis products. For detailed information see www.data-mining-forum.de.

Sponsoring as a means of image advertisement for your company

You would like to become a sponsor of the leading international World Congress DSA. Then we should be pleased if you contacted us under info@data-mining-forum.de.


The papers are published by Springer Publishing House in the Lecture Notes of Computer Sciences and by ibai-publishing house as journal contributions. For more information please visit www.ibai-publishing.org.

Look forward to an outstanding innovative event which we are organizing in one of the most beautiful and exciting cities of the world - New York City.
Contribute to the success of the congress with your scientific or industrial contribution / presentation.

We shall be delighted to welcome you at the World Congress "The Frontier of Intelligent Data and Signal Analysis" DSA 2013.

Looking forward to seeing you,

Yours sincerely,

Prof. Dr. Petra Perner
Chair of the World Congress


Theoretical and Application-oriented Topics:
Agent Data Mining, Algorithms for 1D, 2D and 3D Signal Analysis and Interpretation, Applications in Agriculture, Applications in Biotechnology, Applications in 2D and 3D Cell Images Analysis, Applications in Chemistry, Applications in Crystallography, Applications in Data Mining, Applications in E-Commerce (Mining Log Files), Applications in Intrusion Detection in Networks, Applications in Marketing, Applications in Medicine, Applications in Metreology, Applications in Multimedia Data (Image, Video, Text, Signals), Applications in Process Control and Insurance, Applications in Proteomics, Applications in Quality Management, Applications in Software Testing, Applications in Web-Mining, Applications of Clustering, Applications of Data Mining, Aspects of Data Mining, Aspects of Classification, Aspects of Classification and Prediction, Aspects of Data Mining, Association Mining, Association Rule Mining, Association Rules and Pattern Mining, Attribute Discretization and Data Preparation, Automatic Semantic Annotation of Media Content, Bayesian Models and Methods, Capability Indices, Case-Based Reasoning, Case-Based Reasoning and Associative Memory, Case-Based Reasoning and Learning, Classification, Classification and Image Interpretation, Classification and Interpretation of Images, Text, Video, Classification and Model Estimation, Classification and Prediction, Classification, Retrieval, and Feature Learning, Clustering, Clustering and Association Rules, Clustering and Classification, Clustering and Conceptual Clustering, Clustering: Basics, Content-Based Image Retrieval, Control Charts, Conceptional Learning and Clustering, Decision Trees, Deviation and Novelty Detection, Data Mining, Data Mining and E-Commerce, Data Mining in Marketing, Data Mining in Marketing, Finance and Telecommunication, Data Mining in Medicine, Data Mining in Medicine and Agriculture, Data Mining in Process Control, Industry and Society, Data Mining on Multimedia Data, Data Mining on Signal, Images, Text and Temporal-Spatial Data, Decision Trees, Design of Experiment, Desirabilities, Deviation and Novelty Detection, Discovery of Frequently or Sequential Patterns, Ensemble Classifier Learning, E-Mail, Web Mining, 1D, 2D and 3D Feature Extraction of Texture, Structure and Location, Feature Learning, Feature Grouping, Discretization, Selection and Transformation, Feature Selection, Extraction and Dimensionality Reduction, Frequent and Common Item Set Mining, Frequent Item Set, Sequence Mining, Frequent Pattern Mining, High-Content Analysis of Microscopic Images in Medicine, Biotechnology and Chemistry, Goodness Measures and Evaluation (e.g. False Discovery Rates), Graph Mining, Image Acquisition Procedures for Mass Data Analysis, Image Mining, Image Retrieval, Image Segmentation Algorithms, Inductive Learning Including Decision Tree and Rule Induction Learning, Industrial Applications, Information Retrieval, Intrusion Detection and Networks, Knowledge Extraction from Text, Video, Signals and Images, Knowledge Management and Data Mining, Learning, Learning/Adaption of Recognition and Perception, Learning and Adaptive Control, Learning for Handwriting Recognition, Learning in Image Pre-Processing and Segmentation, Learning in Process Automation, Learning of Action Patterns, Learning of Appropriate Behaviour, Learning of Internal Representations and Models, Learning of Ontologies, Learning of Semantic Inferencing Rules, Learning of Visual Ontologies, Learning Robots, Medical Applications, Medical, Biological, and Environmental Data Mining, Medicine and Biotechnology, Mining Financial or Stockmarket Data, Mining Gene Data Bases and Biological Data Base, Mining Images and Texture, Mining Images in Computer Vision, Mining Images, Temporal-Spatial Data, Images from Remote Sensing, Mining Marketing Data, Mining Motion from Sequence, Mining Signals and Images, Mining Structural Representations such as Log Files, Text Documents and HTML Documents, Mining SPAM, Newsgroup, Blogs, Mining Text Documents, Network Analysis and Intrusion Detection, Neural Methods, Neural Networks Applied to Image Processing and Recognition, Nonlinear Function Learning and Neural Net Based Learning, Novelty and Outlier Detection, Object Matching and Object Tracking in Microscopic and Video Microscopic Images, Organisational Learning and Evolutional Learning, Parallelization of Image Analysis and Interpretation Algorithms, Probabilistic Information Retrieval, Real-Time Event Learning and Detection, Retrieval Methods, Rule Induction and Grammars, Sampling Methods, Selection Bias, Selection with Small Samples, Semantic Tagging of Microscopic Images, 1D, 2D and 3D Shape Analysis and Description, Similarity Measures and Learning of Similarity, Speech Analysis, Statistical and Conceptual Clustering Methods: Basics, Statistical and Evolutionary Learning, Statistical Learning and Neural Net Based Learning, Strategy of Experimentation, Structural Data Mining, Subspace Methods, Support Vector Machines, Symbolic Learning and Neural Networks in Document Processing, Techniques and Developments of Signal and Image Producing Procedures, Telecommunication, Text and Document Mining, Text Mining, Theoretical Aspects of Data Mining, Time Series and Frequent Pattern Mining, Time Series and Sequential Pattern Mining, Transductive Inference, Video Mining, Visualization and Data Mining, Web Mining, Web Mining and Logfile Analysis, ...