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| Titel: |
H-Mine: Fast and space-preserving frequent pattern mining in large databases |
| Auteur: |
Pei, Jian Han, Jiawei Lu, Hongjun Nishio, Shojiro Tang, Shiwei Yang, Dongqing |
| Verschenen in: |
IIE transactions |
| Paginering: | Jaargang 39 (2007) nr. 6 pagina's 593-605 |
| Jaar: |
2007-06 |
| Inhoud: |
In this study, we propose a simple and novel data structure using hyper-links, H-struct, and a new mining algorithm, H-mine, which takes advantage of this data structure and dynamically adjusts links in the mining process. A distinct feature of this method is that it has a very limited and precisely predictable main memory cost and runs very quickly in memory-based settings. Moreover, it can be scaled up to very large databases using database partitioning. When the data set becomes dense, (conditional) FP-trees can be constructed dynamically as part of the mining process. Our study shows that H-mine has an excellent performance for various kinds of data, outperforms currently available algorithms in different settings, and is highly scalable to mining large databases. This study also proposes a new data mining methodology, space-preserving mining, which may have a major impact on the future development of efficient and scalable data mining methods. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
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