Mining Frequent Itemsets Algorithm Based on Compression Matrix
2014 ◽
Vol 556-562
◽
pp. 3501-3505
Keyword(s):
Association rule mining is one of the most important and well researched techniques of data mining. The key procedure of the association rule mining is to find frequent itemsets. In this paper, a new mining frequent itemsets algorithm based on matrix is introduced. Frequent itemsets are obtained by compressing the transaction matrix efficiently by a new strategy. The new algorithm optimizes the known mining frequent itemsets algorithms based on matrix given by some researchers in recent years, which greatly reduces the temporal complexity and spatial complexity. It is more feasible especially when the degrees of the frequent itemsets are high.
2014 ◽
Vol 571-572
◽
pp. 57-62
2014 ◽
Vol 998-999
◽
pp. 899-902
◽
2013 ◽
Vol 327
◽
pp. 197-200
Keyword(s):
2019 ◽
Vol 8
(S2)
◽
pp. 9-12
Keyword(s):
2018 ◽
Vol 189
◽
pp. 10012
◽
2020 ◽
Vol 9
(6)
◽
pp. 890-894
Keyword(s):
2011 ◽
pp. 890-894
Keyword(s):
Keyword(s):