Incremental updating algorithm association rules
The experimental result indicates that the algorithm is effective and feasible.Abstract: Online mining of frequent closed itemsets over streaming data is one of the most important issues in mining data streams.In this paper, we proposed an algorithm named FIN_INCRE based on FIN which updates mined association rules without reinventing the wheel again.
The algorithm exploits lattice properties to limit the search to frequent close itemsets which share at least one item with the new transaction.
Many algorithms came into existence for mining association rules.
Since the databases in the real world are subjected to frequent changes, the algorithms need to be rerun to generate association rules that can reflect record insertions.