Finding Frequent Item Sets from Sparse Matrix
Macau(2009)
Abstract
According to the features of sparse data source while mining association rules, the paper designs a special linked-list unit and two strategies to store data in matrix. A novel algorithm, called SMM (Sparse-Matrix Mining), is proposed to find large item sets from sparse matrix. SMM maps database into a binary sparse matrix and stores compressed data into a linked-list, from which to find large item sets. It uses less I/O and computational time in mining. Experiments show that SMM finds large item sets efficiently and is well scalable.
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Key words
frequent item sets,computational time,compress by column,binary sparse matrix,linked-list,sparse matrices,data compression,set theory,sparse data source,sparse-matrix mining,sparse matrix,data mining,association rules,linked list,sparse data,databases,association rule
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