Discovery of Frequent Itemsets: Frequent Item Tree-Based Approach
Mining frequent patterns in large transactional databases is a highly researched area in the field of data mining. Existing frequent pattern discovering algorithms suffer from many problems regarding the high memory dependency when mining large amount of data, computational and I/O cost. Additionall...
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| Format: | Article |
| Language: | English |
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ITB Journal Publisher
2013-09-01
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| Series: | Journal of ICT Research and Applications |
| Online Access: | https://journals.itb.ac.id/index.php/jictra/article/view/165 |
| _version_ | 1819279089574346752 |
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| author | A. V. Senthil Kumar R. S. D. Wahidabanu |
| author_facet | A. V. Senthil Kumar R. S. D. Wahidabanu |
| author_sort | A. V. Senthil Kumar |
| collection | DOAJ |
| description | Mining frequent patterns in large transactional databases is a highly researched area in the field of data mining. Existing frequent pattern discovering algorithms suffer from many problems regarding the high memory dependency when mining large amount of data, computational and I/O cost. Additionally, the recursive mining process to mine these structures is also too voracious in memory resources. In this paper, we describe a more efficient algorithm for mining complete frequent itemsets from transactional databases. The suggested algorithm is partially based on FP-tree hypothesis and extracts the frequent itemsets directly from the tree. Its memory requirement, which is independent from the number of processed transactions, is another benefit of the new method. We present performance comparisons for our algorithm against the Apriori algorithm and FP-growth. |
| first_indexed | 2024-12-24T00:22:22Z |
| format | Article |
| id | doaj.art-fe6607dc0d30429c966b66a8e0ae2382 |
| institution | Directory Open Access Journal |
| issn | 2337-5787 2338-5499 |
| language | English |
| last_indexed | 2024-12-24T00:22:22Z |
| publishDate | 2013-09-01 |
| publisher | ITB Journal Publisher |
| record_format | Article |
| series | Journal of ICT Research and Applications |
| spelling | doaj.art-fe6607dc0d30429c966b66a8e0ae23822022-12-21T17:24:33ZengITB Journal PublisherJournal of ICT Research and Applications2337-57872338-54992013-09-0111166Discovery of Frequent Itemsets: Frequent Item Tree-Based ApproachA. V. Senthil Kumar0R. S. D. Wahidabanu11Senior Lecturer, Department of MCA, CMS College of Science and Commerce Coimbatore – 641 006. Tamilnadu. India2Head, Department of CSE, Govt. College of Engineering Salem, Tamilnadu, India.Mining frequent patterns in large transactional databases is a highly researched area in the field of data mining. Existing frequent pattern discovering algorithms suffer from many problems regarding the high memory dependency when mining large amount of data, computational and I/O cost. Additionally, the recursive mining process to mine these structures is also too voracious in memory resources. In this paper, we describe a more efficient algorithm for mining complete frequent itemsets from transactional databases. The suggested algorithm is partially based on FP-tree hypothesis and extracts the frequent itemsets directly from the tree. Its memory requirement, which is independent from the number of processed transactions, is another benefit of the new method. We present performance comparisons for our algorithm against the Apriori algorithm and FP-growth.https://journals.itb.ac.id/index.php/jictra/article/view/165 |
| spellingShingle | A. V. Senthil Kumar R. S. D. Wahidabanu Discovery of Frequent Itemsets: Frequent Item Tree-Based Approach Journal of ICT Research and Applications |
| title | Discovery of Frequent Itemsets: Frequent Item Tree-Based Approach |
| title_full | Discovery of Frequent Itemsets: Frequent Item Tree-Based Approach |
| title_fullStr | Discovery of Frequent Itemsets: Frequent Item Tree-Based Approach |
| title_full_unstemmed | Discovery of Frequent Itemsets: Frequent Item Tree-Based Approach |
| title_short | Discovery of Frequent Itemsets: Frequent Item Tree-Based Approach |
| title_sort | discovery of frequent itemsets frequent item tree based approach |
| url | https://journals.itb.ac.id/index.php/jictra/article/view/165 |
| work_keys_str_mv | AT avsenthilkumar discoveryoffrequentitemsetsfrequentitemtreebasedapproach AT rsdwahidabanu discoveryoffrequentitemsetsfrequentitemtreebasedapproach |