INCREMENTAL MINING OF ASSOCIATION RULES USING DATA CUBES

摘要

An incremental updating algorithm for the maintenance of previously discovered association rules is applied on data cubes. Previous research work concentrated on the development of incremental algorithms working on flat data ; i.e. the database files. Due to the huge amounts of data usually in process, using the data cubes accelerates the job and avoids scanning the whole database after every update on the data. The approach also suggests a way to practically perform the incremental mining process without affecting the original (functioning) database. Previous methods required tagging new records to count them in the incremental algorithm, here we overcome this point.