Abstract
This paper proposes a new algorithm for mining association rules. In order to calculate itemsets support, this paper puts forward the concept of database characteristic matrix and characteristic vector, and emerges an algorithm for mining association rules based on the characteristic matrix. This algorithm needs to traverse the database one time only, and the database operation has been reduced greatly. Based on the characteristic vector inner product, an itemset support can be obtained and the efficiency of the algorithm has been improved.
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Tong, Y., Meide, X. (2016). An Algorithm for Mining Association Rules Based on the Database Characteristic Matrix. In: Qi, E. (eds) Proceedings of the 6th International Asia Conference on Industrial Engineering and Management Innovation. Atlantis Press, Paris. https://doi.org/10.2991/978-94-6239-145-1_8
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DOI: https://doi.org/10.2991/978-94-6239-145-1_8
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