MPPES 2013 - IEEE Workshop on Mining Performance Patterns in Elite Sports 2013

Papers will discuss related topics of the applications, current challenges, and possibly the future of using advanced data analytics techniques in knowledge discovery and knowledge generation in elite sports.
Topics
Topics of interest include but are not limited to:
Overview of data mining in elite sports
Frameworks and challenges to bring together data mining and sport science
Application of existing data mining and machine learning techniques in sports data analysis
Challenges/benefits of using major and current data mining and machine learning techniques in sports. For example:
Supervised learners
Unsupervised learners
Probabilistic learners/reasoners
Rule miners
Statistical relationship estimators
Adapting data mining and machine learning techniques for sports data analysis
Selecting specific data mining techniques for problem types in sports
Outlier modelling in sports data
Data staging (collection and pre-processing) for sports data mining
Real-time data mining-based decision support tools in sports
Visualization of sports performance patterns
Video and image mining in sports
Text mining (and its applications) in elite sports
Preparation and interpretation of sports data mining results analysis.
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