An effective algorithm for mining sequential generators

作者：Yi, Shengwei^*; Zhao, Tianheng; Zhang, Yuanyuan; Ma, Shilong; Che, Zhanbin

来源：International Conference on Advanced in Control Engineering and Information Science (CEIS), Dali, PEOPLES R CHINA, 2011-08-18 To 2011-08-19.

DOI：10.1016/j.proeng.2011.08.684

• Sequential Generators
• Algorithms
• Safe Pruning
• Generator Checking

Mining frequent sequences patterns invokes the interests of many searchers. However, the result set of frequent sequences is tremendous. While frequent sequential generator patterns can compact the result set of frequent sequences greatly and are superior to the frequent sequential closed patterns in classification and model selection. The existing sequential generator patterns mining algorithm fails to make full use of the relationship between a sequence and its subsequence. And when mining the frequent sequential generators, the existing algorithms are ineffective and inefficient. In order to resolve this problem, an effective and efficient algorithm is presented. A lot of experiments about the performance on datasets are conducted. The results show that the algorithm proposed is better than the existing algorithms for mining the sequential generators.

• 出版日期2011
• 单位北京航空航天大学; 软件开发环境国家重点实验室