Research on Apriori Algorithm Based on Matrix Compression in Basketball Techniques and Tactics

Apriori algorithm is the most commonly used algorithm for mining frequent closed itemsets, which core idea is to generate frequent itemsets by computing support and pruning operations. However, the traditional Apriori algorithm has many shortcomings, an Apriori algorithm based on matrix compression is proposed, and the method of association and design of various technical actions in basketball matches is introduced. First, the transaction database is converted to Boolean matrix, which reduces the number of scans times and improves the time running efficiency of the algorithm. In addition, in order to improve space efficiency, the operation of deleting infrequent itemsets is added, and the generation of candidate sets is greatly reduced. Instance analysis and experimental results show that the improved algorithm has better performance than the existing algorithm, and can effectively improve the algorithm execution efficiency. And it can be effectively used to mine the potential relationship of basketball game technical movements, which is of great importance to the research of basketball game technical movements.

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