MPRSS 2014 - European Conference on Data Analysis 2014

The scientific program of the conference will include invited sessions and contributed presentations covering a broad range of topics. A special emphasis is laid on research on and development of innovative tools, techniques and strategies that address current challenges in the data analysis process. We solicit contributions from scholars and practitioners on all domains where statistical and data analytical methods are being developed and applied. We welcome contributions from all areas, in particular the following fields.
Data Analysis and Statistics
Machine Learning and Knowledge Discovery
Data Analysis in Marketing
Data Analysis in Finance and Economics
Data Analysis in Medicine and the Life Sciences
Data Analysis in the Social, Behavioral and Health Care Sciences
Data Analysis in Interdisciplinary Domains including Archaeology, Astronomy, Education, Engineering, Geosciences, Linguistics, Logistics, Musicology, Natural Sciences
Topics in these areas include but are not restricted to:
Theory and Methods:
Classification and Regression-Type Approaches
Decision Trees and Forests
Dimensionality Reduction
Ensemble Methods
Feature Space Reduction
Frequent Pattern Mining
Knowledge Representation and Discovery
Latent Variable Models
Machine Learning
Methods for Analyzing and Representing Social Networks and Other Large Graphs
Methods for Personalization and Recommender Systems
Methods for Preference and Positioning Analysis
Mixture Models
Multivariate Statistical Analysis
Relational Learning
Regulation Network Inference
Statistical Natural Language Processing
Statistical Validation
Time Series, Longitudinal and Panel Data Analysis
Data Exploration:
Big Data Analytics
Data Preparation and Normalization
Data Sonification
Data Visualization
Exploratory Data Analysis and Data Mining
Text Mining
Web Mining
Applications:
Banking and Other Financial Institutions
Business Intelligence
Costumer Relationship Management
Credit Risk Management
Data Mining in Finance
Education studies
Image Analysis and Computer Vision
Life Sciences, Biostatistics and Bioinformatics
Market Risk Management
Medical and Health Sciences
Natural Sciences and Geography
Political Science and Sociology
Production, Controlling and Logistics
Psychology
Subject Indexing and Library Science
ECDA 2014 also incorporates a Workshop on Library and Information Science (LIS 2014), soliciting contributions on the role of classification and data analysis in this domain.