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An Efficient Sequential Pattern Mining Algorithm Based on the 2-Sequence Matrix
Sequential pattern mining has become more and more popular in recent years due to its wide applications and the fact that it can find more information than association rules. Two famous algorithms in sequential pattern mining are AprioriAll and PrefixSpan. These two algorithms not only need to scan...
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| creator | Chia-Ying Hsieh Don-Lin Yang Jungpin Wu |
| description | Sequential pattern mining has become more and more popular in recent years due to its wide applications and the fact that it can find more information than association rules. Two famous algorithms in sequential pattern mining are AprioriAll and PrefixSpan. These two algorithms not only need to scan a database or projected-databases many times, but also require setting a minimal support threshold to prune infrequent data to obtain useful sequential patterns efficiently. In addition, they must rescan the database if new items or sequences are added. In this paper, we propose a novel algorithm called efficient sequential pattern enumeration (ESPE) to solve the above problems. In addition, our method can be applied in many applications, such as for the itemsets appearing at the same time in a sequence. In our experiments, we show that the performance of ESPE is better than the other two methods using various datasets. |
| doi_str_mv | 10.1109/ICDMW.2008.82 |
| format | conference_proceeding |
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| identifier | ISSN: 2375-9232 |
| ispartof | 2008 IEEE International Conference on Data Mining Workshops, 2008, p.583-591 |
| issn | 2375-9232 2375-9259 |
| language | eng |
| recordid | cdi_ieee_primary_4733982 |
| source | IEEE Xplore All Conference Series |
| subjects | Application software association rule Association rules Bioinformatics candidate enumeration Computer science Conferences Data engineering Data mining Itemsets minimum support Sequential pattern Statistics |
| title | An Efficient Sequential Pattern Mining Algorithm Based on the 2-Sequence Matrix |
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