Paper submission: March 31, 2010.

The International Conference on Machine Learning and Data Analysis is the premier forum for the presentation of new advances and research results in the fields of Machine Learning and Data Analysis.

Topics of interest for submission include, but are not limited to:

• Analysis of Time Series, Longitudinal and Panel Data
• Aspects of data mining
• Association rules
• Automatic semantic annotation of media content
• Bayesian models and methods
• Case-based reasoning and learning
• Case-cased reasoning and associative memory
• Classification and interpretation of images, text, video
• Classification and model estimation
• Classification and Regression
• Cluster Analysis and Similarity Structures
• Computational Intelligence
• Conceptional learning and clustering
• Content-based image retrieval
• Data Preprocessing and Information Extraction
• Data Visualization and Scaling Methods
• Decision trees
• Deviation and novelty detection
• Ensemble methods
• Exploratory Data Analysis and Data Mining
• Feature grouping, discretization, selection and transformation
• Feature learning
• Frequent pattern mining
• Goodness measures and evaluation
• High-content analysis
• Inductive learning including decision tree and rule induction learning
• Knowledge extraction from text, video, signals and images
• Knowledge Representation and Knowledge Discovery
• 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/adaption of recognition and perception
• Mining images and texture
• Mining images, temporal-spatial data, images from remote sensing
• Mining motion from sequence
• Mining structural representations such as log files, text documents and htm- documents
• Mining text documents
• Mixture Analysis in Clustering
• Network analysis and intrusion detection
• Neural methods
• Nonlinear function learning and neural net based learning
• Online Algorithms and Data Streams
• Organisational learning and evolutional learning
• Probabilistic information retrieval
• Real-time event learning and detection
• Retrieval methods
• Rule induction and grammars
• Sampling methods
• Selection bias
• Selection with small samples
• Similarity measures and learning of similarity
• Speech analysis
• Statistical and conceptual clustering methods
• Statistical and evolutionary learning
• Statistical learning and neural net based learning
• Statistical Relational Learning
• Subspace methods
• Supervised Classification, Discrimination and Pattern Recognition
• Support vector machines
• Symbolic learning and neural networks in document processing
• Text mining
• Time series and sequential pattern mining
• Tools for Intelligent Data Analysis
• Typing for Modeling
• Video mining
• Visualization and data mining

Подробности на сайте Конференции

Организаторы приглашают российских социологов принять участие в Конференции.