Discovering Periodic-Frequent Patterns in Transactional Databases.

Since mining frequent patterns from transactional databases involves an exponential mining space and generates a huge number of patterns, efficient discovery of user-interest-based frequent pattern set becomes the first priority for a mining algorithm. In many real-world scenarios it is often sufficient to mine a small interesting representative subset of frequent patterns. Temporal periodicity of pattern appearance can be regarded as an important criterion for measuring the interestingness of frequent patterns in several applications. A frequent pattern can be said periodic-frequent if it appears at a regular interval given by the user in the database. In this paper, we introduce a novel concept of mining periodic-frequent patterns from transactional databases. We use an efficient tree-based data structure, called Periodic-frequent pattern tree (PF-tree in short), that captures the database contents in a highly compact manner and enables a pattern growth mining technique to generate ...

• Type: Conference
• Year: 2009
• Where: PAKDD
• Authors: Byeong-Soo Jeong, Chowdhury Farhan Ahmed, Syed Khairuzzaman Tanbeer, Young-Koo Lee
• Keywords: Computer Science, Mining Frequent Patterns, Mining Periodic-frequent Patterns, PAKDD 2009, Pattern Growth Mining