|
| This Article | ||
| | ||
| Share | ||
| Bibliographic References | ||
| Add to: | ||
| | ||
| Search | ||
| ||
First IEEE International Conference on Data Mining (ICDM'01)
San Jose, California
November 29-December 02
ISBN: 0-7695-1119-8
| ASCII Text | x | ||
| Qinghua Zou, Wesley Chu, David Johnson, Henry Chiu, "A Pattern Decomposition (PD) Algorithm for Finding All Frequent Patterns in Large Datasets," Data Mining, IEEE International Conference on, pp. 673, First IEEE International Conference on Data Mining (ICDM'01), 2001. | |||
| BibTex | x | ||
| @article{ 10.1109/ICDM.2001.989603, author = {Qinghua Zou and Wesley Chu and David Johnson and Henry Chiu}, title = {A Pattern Decomposition (PD) Algorithm for Finding All Frequent Patterns in Large Datasets}, journal ={Data Mining, IEEE International Conference on}, volume = {0}, year = {2001}, isbn = {0-7695-1119-8}, pages = {673}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2001.989603}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Data Mining, IEEE International Conference on TI - A Pattern Decomposition (PD) Algorithm for Finding All Frequent Patterns in Large Datasets SN - 0-7695-1119-8 SP EP A1 - Qinghua Zou, A1 - Wesley Chu, A1 - David Johnson, A1 - Henry Chiu, PY - 2001 VL - 0 JA - Data Mining, IEEE International Conference on ER - | |||
Efficient algorithms to mine frequent patterns are crucial to many tasks in data mining. Since the Apriori algorithm was proposed in 1994, there have been several methods proposed to improve its performance. However, most still adopt its candidate set generation-and-test approach. We propose a pattern decomposition (PD) algorithm that can significantly reduce the size of the dataset on each pass making it more efficient to mine frequent patterns in a large dataset. The proposed algorithm avoids the costly process of candidate set generation and saves time by reducing dataset. Our empirical evaluation shows that the algorithm outperforms Apriori by one order of magnitude and is faster than FP-tree. Further, PD is more scalable than both Apriori and FP-tree.
Citation:
Qinghua Zou, Wesley Chu, David Johnson, Henry Chiu, "A Pattern Decomposition (PD) Algorithm for Finding All Frequent Patterns in Large Datasets," icdm, pp.673, First IEEE International Conference on Data Mining (ICDM'01), 2001
Usage of this product signifies your acceptance of the Terms of Use.
