EFP-M2: Efficient model for mining frequent patterns in transactional database

• Main Authors: Herawan, Tutut, Noraziah, Ahmad, Zailani, Abdullah, Mustafa, Mat Deris, H. Abawajyd, Jemal
• Format: Conference or Workshop Item
• Language: English
• Published: Springer Nature Switzerland 2012
• Subjects: QA76 Computer software
• Online Access: http://umpir.ump.edu.my/id/eprint/26642/1/EFP-M2-%20Efficient%20model%20for%20mining%20frequent%20patterns.pdf; http://umpir.ump.edu.my/id/eprint/26642/; https://doi.org/10.1007/978-3-642-34707-8_4
• Institution: Universiti Malaysia Pahang

Discovering frequent patterns plays an essential role in many data mining applications. The aim of frequent patterns is to obtain the information about the most common patterns that appeared together. However, designing an efficient model to mine these patterns is still demanding due to the capacity of current database size. Therefore, we propose an Efficient Frequent Pattern Mining Model (EFP-M2) to mine the frequent patterns in timely manner. The result shows that the algorithm in EFP-M2l is outperformed at least at 2 orders of magnitudes against the benchmarked FP-Growth.