Mining distinguishing subsequence patterns with nonoverlapping condition-Reference-Cited by-同舟云学术

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Mining distinguishing subsequence patterns with nonoverlapping condition

Published:2018-01-09 Issue:S3 Volume:22 Page:5905-5917
ISSN:1386-7857
Container-title:Cluster Computing
language:en
Short-container-title:Cluster Comput

Author:

Wu Youxi,Wang Yuehua,Liu Jingyu,Yu Ming,Liu Jing,Li Yan

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hebei Province

Science and the Technology Project of Hebei Province

Graduate Student Innovation Program of Hebei Province

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Software

Link

http://link.springer.com/content/pdf/10.1007/s10586-017-1671-0.pdf

Reference29 articles.

1. Malarvizhi, S.P., Sathiyabhama, B.: Frequent pagesets from web log by enhanced weighted association rule mining. Clust. Comput. 19(1), 269–277 (2016)

2. Ding, B., Lo, D., Han, J., et al.: Efficient mining of closed repetitive gapped subsequences from a sequence database. In: IEEE 25th International Conference on Data Engineering, pp. 1024–1035 (2009)

3. Zhang, S., Du, Z., Wang, J.T.: New techniques for mining frequent patterns in unordered trees. IEEE Trans. Cybern. 45(6), 1113–1125 (2015)

4. Tan, C., Min, F., Wang, M., et al.: Discovering patterns with weak-wildcard gaps. IEEE Access 4, 4922–4932 (2016)

5. Feng, Y., Ji, M., Xiao, J., et al.: Mining spatial-temporal patterns and structural sparsity for human motion data denoising. IEEE Trans. Cybern. 45(12), 2693–2706 (2015)

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