A condensed representation to find frequent patterns
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Advanced Scout: Data Mining and Knowledge Discovery in NBA Data
Data Mining and Knowledge Discovery
Mining All Non-derivable Frequent Itemsets
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Knowledge Discovery in Databases: An Attribute-Oriented Approach
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
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BNCOD 18 Proceedings of the 18th British National Conference on Databases: Advances in Databases
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
A Novel Framework for Semantic Annotation and Personalized Retrieval of Sports Video
IEEE Transactions on Multimedia
The measurement of stakeholder salience: a strategy for the exploration of stakeholder theories
International Journal of Data Analysis Techniques and Strategies
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Frequent pattern evaluation is imperative for cricket match data to develop more proficient coaching strategies and progress the performance of individual players. The rapid growth in size of the match database far exceeds the human ability to analyse, thus creating an opportunity to extract knowledge from this database. Very few research efforts have been carried out on sports data (especially on cricket) and none of them focused on play patterns. Our work emphasises play patterns to discover interesting patterns from cricket matches and evaluate those patterns to turn them into knowledge that can further be used to modify the coaching process and play styles. Since real-time cricket data are too complex, an object-relational model is used here. In this work, Principal Component Analysis (PCA) is used to reduce high dimensional match data set into lower dimensional data set in order to improve predictive performance and to detect frequently occurring play patterns.