SEQUEST: Mining frequent subsequences using DMA strips
Sequential patterns exist in data such as DNA string databases, occurrences of recurrent illness, etc. In this study, we present an algorithm, SEQUEST, to mine frequent subsequences from sequential patterns. The challenges of mining a very large database of sequences is computationally expensive and...
| Main Authors: | , , , |
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| Format: | Conference Paper |
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WIT Press
2006
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| Online Access: | http://library.witpress.com/pages/listPapers.asp?q_bid=357 http://hdl.handle.net/20.500.11937/33029 |
| _version_ | 1848753832584019968 |
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| author | Tan, H. Dillon, Tharam S. Hadzic, Fedja Chang, Elizabeth |
| author_facet | Tan, H. Dillon, Tharam S. Hadzic, Fedja Chang, Elizabeth |
| author_sort | Tan, H. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Sequential patterns exist in data such as DNA string databases, occurrences of recurrent illness, etc. In this study, we present an algorithm, SEQUEST, to mine frequent subsequences from sequential patterns. The challenges of mining a very large database of sequences is computationally expensive and require large memory space. SEQUEST uses a Direct Memory Access Strips (DMA-Strips) structure to efficiently generate candidate subsequences. DMA-Strips structure provides direct access to each item to be manipulated and thus is optimized for speed and space performance. In addition, the proposed technique uses a hybrid principle of frequency counting by the vertical join approach and candidate generation by structure guided method. The structure guided method is adapted from the TMG approach used for enumerating subtrees in our previous work [8]. Experiments utilizing very large databases of sequences which compare our technique with the existing technique, PLWAP [4], demonstrate the effectiveness of our proposed technique. |
| first_indexed | 2025-11-14T08:30:47Z |
| format | Conference Paper |
| id | curtin-20.500.11937-33029 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:30:47Z |
| publishDate | 2006 |
| publisher | WIT Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-330292017-01-30T13:34:32Z SEQUEST: Mining frequent subsequences using DMA strips Tan, H. Dillon, Tharam S. Hadzic, Fedja Chang, Elizabeth data mining sequential strips sequence mining frequent subsequences SEQUEST DMA-strips phylogenic tree Sequential patterns exist in data such as DNA string databases, occurrences of recurrent illness, etc. In this study, we present an algorithm, SEQUEST, to mine frequent subsequences from sequential patterns. The challenges of mining a very large database of sequences is computationally expensive and require large memory space. SEQUEST uses a Direct Memory Access Strips (DMA-Strips) structure to efficiently generate candidate subsequences. DMA-Strips structure provides direct access to each item to be manipulated and thus is optimized for speed and space performance. In addition, the proposed technique uses a hybrid principle of frequency counting by the vertical join approach and candidate generation by structure guided method. The structure guided method is adapted from the TMG approach used for enumerating subtrees in our previous work [8]. Experiments utilizing very large databases of sequences which compare our technique with the existing technique, PLWAP [4], demonstrate the effectiveness of our proposed technique. 2006 Conference Paper http://hdl.handle.net/20.500.11937/33029 http://library.witpress.com/pages/listPapers.asp?q_bid=357 WIT Press fulltext |
| spellingShingle | data mining sequential strips sequence mining frequent subsequences SEQUEST DMA-strips phylogenic tree Tan, H. Dillon, Tharam S. Hadzic, Fedja Chang, Elizabeth SEQUEST: Mining frequent subsequences using DMA strips |
| title | SEQUEST: Mining frequent subsequences using DMA strips |
| title_full | SEQUEST: Mining frequent subsequences using DMA strips |
| title_fullStr | SEQUEST: Mining frequent subsequences using DMA strips |
| title_full_unstemmed | SEQUEST: Mining frequent subsequences using DMA strips |
| title_short | SEQUEST: Mining frequent subsequences using DMA strips |
| title_sort | sequest: mining frequent subsequences using dma strips |
| topic | data mining sequential strips sequence mining frequent subsequences SEQUEST DMA-strips phylogenic tree |
| url | http://library.witpress.com/pages/listPapers.asp?q_bid=357 http://hdl.handle.net/20.500.11937/33029 |