RP-Tree: A Tree Structure to Discover Regular Patterns in Transactional Database

Syed Khairuzzaman Tanbeer, Chowdhury Farhan Ahmed, Byeong-Soo Jeong, Young-Koo Lee

Abstract: Temporal regularity of pattern appearance can be regarded as an important criterion for measuring the interestingness in several applications like market basket analysis, web administration, gene data analysis, network monitoring, and stock market. Even though there have been some efforts to discover periodic patterns in time-series and sequential data, none of the existing works is appropriate for discovering the patterns that occur regularly in a transactional database. Therefore, in this paper, we introduce a novel concept of mining regular patterns from transactional databases and propose an efficient data structure, called Regular Pattern tree (RP-tree in short), that enables a pattern growth-based mining technique to generate the complete set of regular patterns in a database for a user-given regularity threshold. Our comprehensive experimental study shows that RP-tree is both time and memory efficient in finding regular pattern.