ICMLDA 2012 - International Conference on Machine Learning and Data Analysis (ICMLDA 2012)

The VIII. 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. The conference will bring together leading researchers, engineers and scientists in the domain of interest from around the world. 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 of microscopic images in medicine, biotechnology and chemistry
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 robots
Learning/adaption of recognition and perception
Mining financial or stockmarket data
Mining gene data bases and biological data bases
Mining images and texture
Mining images in computer vision
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

Applications of Machine Learning and Data Analysis
Marketing and Management Science
Banking and Finance
Business Intelligence and Personalization
Data Analysis in Retailing
Econometrics and Operations Research
Image and Signal Analysis
Biostatistics and Bioinformatics
Medical and Health Sciences
Text Mining, Web Mining, and the Semantic Web
Statistical Natural Language Processing
Linguistics
Subject Indexing and Library Science
Statistical Musicology
Archaeology and Archaeometry
Psychology
Data Analysis in Higher Education Contact us: info-AT-waset.org