The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop
Top-k frequent pattern discovery is indeed an association analysis concerning automatic extraction of the k most correlated and interesting patterns from large databases. Current studies in association mining concentrate on how to effectively find all objects that are frequently co-occurring. Given...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Faculty of Computer and Mathematical Sciences
2014
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| Online Access: | https://ir.uitm.edu.my/id/eprint/12418/ |
| _version_ | 1848803151489007616 |
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| author | Kerdprasop, Nittaya Kerdprasop, Kittisak |
| author_facet | Kerdprasop, Nittaya Kerdprasop, Kittisak |
| author_sort | Kerdprasop, Nittaya |
| building | UiTM Institutional Repository |
| collection | Online Access |
| description | Top-k frequent pattern discovery is indeed an association analysis concerning automatic extraction of the k most correlated and interesting patterns from large databases. Current studies in association mining concentrate on how to effectively find all objects that are frequently co-occurring. Given a set of objects with m features, there are almost 2m frequent patterns to consider. For DNA data that are normally very high in dimensionality, frequent pattern discovery from genetic data is obviously a computationally expensive problem. We therefore devise an approximate approach to tackle this problem. We propose
an approximate method based on the window sliding concept to estimate data density and obtain data characteristics from a small set of samples. Then we draw a set of representatives with reservoir sampling technique. These representatives are subsequently used in the main process of frequent pattern mining. Our designed algorithm had been implemented with the Erlang language, which is the functional programming paradigm with inherent support for pattern matching. The experimental results confirm the efficiency and reliability of our approximate method. |
| first_indexed | 2025-11-14T21:34:41Z |
| format | Article |
| id | uitm-12418 |
| institution | Universiti Teknologi MARA |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T21:34:41Z |
| publishDate | 2014 |
| publisher | Faculty of Computer and Mathematical Sciences |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uitm-124182022-06-14T02:48:32Z https://ir.uitm.edu.my/id/eprint/12418/ The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop mjoc Kerdprasop, Nittaya Kerdprasop, Kittisak Top-k frequent pattern discovery is indeed an association analysis concerning automatic extraction of the k most correlated and interesting patterns from large databases. Current studies in association mining concentrate on how to effectively find all objects that are frequently co-occurring. Given a set of objects with m features, there are almost 2m frequent patterns to consider. For DNA data that are normally very high in dimensionality, frequent pattern discovery from genetic data is obviously a computationally expensive problem. We therefore devise an approximate approach to tackle this problem. We propose an approximate method based on the window sliding concept to estimate data density and obtain data characteristics from a small set of samples. Then we draw a set of representatives with reservoir sampling technique. These representatives are subsequently used in the main process of frequent pattern mining. Our designed algorithm had been implemented with the Erlang language, which is the functional programming paradigm with inherent support for pattern matching. The experimental results confirm the efficiency and reliability of our approximate method. Faculty of Computer and Mathematical Sciences 2014 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/12418/1/12418.pdf Kerdprasop, Nittaya and Kerdprasop, Kittisak (2014) The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop. (2014) Malaysian Journal of Computing (MJoC) <https://ir.uitm.edu.my/view/publication/Malaysian_Journal_of_Computing_=28MJoC=29.html>, 2 (2). pp. 1-12. ISSN 2231-7473 https://mjoc.uitm.edu.my/ |
| spellingShingle | Kerdprasop, Nittaya Kerdprasop, Kittisak The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop |
| title | The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop |
| title_full | The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop |
| title_fullStr | The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop |
| title_full_unstemmed | The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop |
| title_short | The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop |
| title_sort | discovery of top-k dna frequent patterns with approximate method / nittaya kerdprasop and kittisak kerdprasop |
| url | https://ir.uitm.edu.my/id/eprint/12418/ https://ir.uitm.edu.my/id/eprint/12418/ |