Mining frequent itemsets over data stream by matrix
Cheng Liang · Jisuanji kexue yu tansuo · 2008
Mining frequent itemsets is a basic task of the data stream mining. Recently many approximate algorithms can mine frequent itemsets over data stream. However, these algorithms still can not efficiently reduce space and time cost. To improve the efficiency of mining frequent itemsets over data stream, matrix is imported as the synopsis data structure and a new algorithm of mining frequent itemsets is presented. Finally, experiments prove the efficiency of this algorithm.