A Parallel Mining Algorithm for Maximum Erasable Itemset Based on Multi-core Processor
Mining the erasable itemset is an interesting research domain, which has been applied to solve the problem of how to efficiently use limited funds to optimise production in economic crisis. After the problem of mining the erasable itemset was posed, researchers have proposed many algorithms to solve...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2024-01-01
|
| Series: | Tehnički Vjesnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/455009 |
| _version_ | 1797206088070725632 |
|---|---|
| author | Qunli Zhao Hesheng Cheng Chen Shen |
| author_facet | Qunli Zhao Hesheng Cheng Chen Shen |
| author_sort | Qunli Zhao |
| collection | DOAJ |
| description | Mining the erasable itemset is an interesting research domain, which has been applied to solve the problem of how to efficiently use limited funds to optimise production in economic crisis. After the problem of mining the erasable itemset was posed, researchers have proposed many algorithms to solve it, among which mining the maximum erasable itemset is a significant direction for research. Since all subsets of the maximum erasable itemset are erasable itemsets, all erasable itemsets can be obtained by mining the maximum erasable itemset, which reduces both the quantity of candidate and resultant itemsets generated during the mining process. However, computing many itemset values still takes a lot of CPU time when mining huge amounts of data. And it is difficult to solve the problem quickly with sequential algorithms. Therefore, this proposed study presents a parallel algorithm for the mining of maximum erasable itemsets, called PAMMEI, based on a multi-core processor platform. The algorithm divides the entire mining task into multiple subtasks and assigns them to multiple processor cores for parallel execution, while using an efficient pruning strategy to downsize the space to be searched and increase the mining speed. To verify the efficiency of the PAMMEI algorithm, the paper compares it with most advanced algorithms. The experimental results show that PAMMEI is superior to the comparable algorithms with respect to runtime, memory usage and scalability. |
| first_indexed | 2024-04-24T09:01:27Z |
| format | Article |
| id | doaj.art-1548ff094b8b45858383c84676e846e6 |
| institution | Directory Open Access Journal |
| issn | 1330-3651 1848-6339 |
| language | English |
| last_indexed | 2024-04-24T09:01:27Z |
| publishDate | 2024-01-01 |
| publisher | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
| record_format | Article |
| series | Tehnički Vjesnik |
| spelling | doaj.art-1548ff094b8b45858383c84676e846e62024-04-15T19:25:59ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392024-01-0131261862710.17559/TV-20230719000815A Parallel Mining Algorithm for Maximum Erasable Itemset Based on Multi-core ProcessorQunli Zhao0Hesheng Cheng1Chen Shen2School of Computer and Artificial Intelligence, Hefei Normal University, Hefei, China 230061School of Computer and Artificial Intelligence, Hefei Normal University, Hefei, China 230061School of Computer and Artificial Intelligence, Hefei Normal University, Hefei, China 230061Mining the erasable itemset is an interesting research domain, which has been applied to solve the problem of how to efficiently use limited funds to optimise production in economic crisis. After the problem of mining the erasable itemset was posed, researchers have proposed many algorithms to solve it, among which mining the maximum erasable itemset is a significant direction for research. Since all subsets of the maximum erasable itemset are erasable itemsets, all erasable itemsets can be obtained by mining the maximum erasable itemset, which reduces both the quantity of candidate and resultant itemsets generated during the mining process. However, computing many itemset values still takes a lot of CPU time when mining huge amounts of data. And it is difficult to solve the problem quickly with sequential algorithms. Therefore, this proposed study presents a parallel algorithm for the mining of maximum erasable itemsets, called PAMMEI, based on a multi-core processor platform. The algorithm divides the entire mining task into multiple subtasks and assigns them to multiple processor cores for parallel execution, while using an efficient pruning strategy to downsize the space to be searched and increase the mining speed. To verify the efficiency of the PAMMEI algorithm, the paper compares it with most advanced algorithms. The experimental results show that PAMMEI is superior to the comparable algorithms with respect to runtime, memory usage and scalability.https://hrcak.srce.hr/file/455009data miningerasable itemsetmaximum erasable itemsetmulti-core platformproduct sets |
| spellingShingle | Qunli Zhao Hesheng Cheng Chen Shen A Parallel Mining Algorithm for Maximum Erasable Itemset Based on Multi-core Processor Tehnički Vjesnik data mining erasable itemset maximum erasable itemset multi-core platform product sets |
| title | A Parallel Mining Algorithm for Maximum Erasable Itemset Based on Multi-core Processor |
| title_full | A Parallel Mining Algorithm for Maximum Erasable Itemset Based on Multi-core Processor |
| title_fullStr | A Parallel Mining Algorithm for Maximum Erasable Itemset Based on Multi-core Processor |
| title_full_unstemmed | A Parallel Mining Algorithm for Maximum Erasable Itemset Based on Multi-core Processor |
| title_short | A Parallel Mining Algorithm for Maximum Erasable Itemset Based on Multi-core Processor |
| title_sort | parallel mining algorithm for maximum erasable itemset based on multi core processor |
| topic | data mining erasable itemset maximum erasable itemset multi-core platform product sets |
| url | https://hrcak.srce.hr/file/455009 |
| work_keys_str_mv | AT qunlizhao aparallelminingalgorithmformaximumerasableitemsetbasedonmulticoreprocessor AT heshengcheng aparallelminingalgorithmformaximumerasableitemsetbasedonmulticoreprocessor AT chenshen aparallelminingalgorithmformaximumerasableitemsetbasedonmulticoreprocessor AT qunlizhao parallelminingalgorithmformaximumerasableitemsetbasedonmulticoreprocessor AT heshengcheng parallelminingalgorithmformaximumerasableitemsetbasedonmulticoreprocessor AT chenshen parallelminingalgorithmformaximumerasableitemsetbasedonmulticoreprocessor |