Mining incrementally closed item sets with constructive pattern set

Abstract

Mining incrementally closed item sets is an essential problem in data mining. Once closed item sets and their frequencies are found, the frequentation of a found closed item set is always determined. In recent times, concept lattice has been used as an intermediate structure for the purpose of mining incrementally (frequent) closed sets. However, lattice operations are very time-consuming when data fluctuates as well as the memory for lattice is consumed a lot when data becomes large. This paper proposes an intermediate structure called constructive set to produce closed sets along with their occurrence frequencies. The constructive set is constructed from a set of group patterns – an extended form of bit chains. This paper also proposes algorithms based on the constructive set for mining incrementally closed sets when adding and removing transactions. The proposed algorithms along with storing and calculating on bit data have significant advantages shown through experiments and comparisons.