Mining Closed-Regular Patterns in Incremental Transactional Databases using Vertical Data Format

Regular pattern mining on Incremental Databases is a novel approach in Data Mining Research. Recently closed item set mining has gained lot of consideration in mining process. In this paper we propose a new mining method called CRPMID (Closed-regular Pattern Mining on Incremental Databases) with sliding window technique using Vertical Data format. This method generates complete set of closed-regular patterns with support and regularity threshold values. Our Experimental results show that CRPMID method is efficient in both memory usage and execution time. General Terms Algorithms