EFP-M2: Efficient model for mining frequent patterns in transactional database
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...
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| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
Springer Nature Switzerland
2012
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| Subjects: | |
| 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 |
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| Institution: | Universiti Malaysia Pahang |
| Language: | English |
| Summary: | 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. |
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