期刊文献+

IDSG:一种新的频繁序列挖掘算法

IDSG:a new algorithm for mining frequent sequences
下载PDF
导出
摘要 在研究已有算法的基础上提出了一种频繁序列挖掘算法IDSG.该算法通过在频繁项(而不是频繁项集,即无需先求出所有频繁项集)间建立关联图,并在垂直数据库表达的基础上,借助简单的时态连接得到频繁序列完全集.整个过程只需扫描原始数据库两遍,有效减少磁盘I/O.另外,优化策略的正确运用,有助于减少候选序列的个数.分析及实验表明,较之同类算法,算法IDSG在效率上有了明显提高. A new algorithm of frequent sequence mining, IDSG,, is proposed. IDSG finds out the frequent sequences using association graph among frequent items. The whole process only needs to scan the original database twice and it can decreases the disk I/O efficiently. In addition, the properly utilize of optimization strategy is benefit to decrease the number of candidate sequences. Compared with other algorithms of the same kind, analysis and experiment results show that algorithm IDSG is highly improved.
出处 《湖北大学学报(自然科学版)》 CAS 北大核心 2008年第1期24-28,38,共6页 Journal of Hubei University:Natural Science
基金 国家自然科学基金(60603069) 湖北省自然科学基金(2006ABA016) 湖北省教育厅科学研究计划项目(D20060003)
关键词 序列模式 频繁序列 算法 sequential patterns frequent sequence algorithm
  • 相关文献

参考文献7

  • 1Agrawal R, Srikant R. Mining sequential patterns[C]. Proc 1995 Int Conf Data Engineering (ICDE'95). Taipei: IEEE Computer Society Press, 1995 : 3-14.
  • 2Yen S J. An Efficient Approach to Discovering Knowledge from Large Databases[C]. Proceedings of 4^th International Conference on Parallel and Distributed Information Systems(PDIS'9 6), 1996.
  • 3Srikant R, Agrawal R. Mining sequential patterns: Generalizations and performance improvements[C]. Proc of the 5th Int Conf on Extending Database Technology (EDBT'96). Berlin: Springer-Verlag, 1996:3-17.
  • 4Zaki M. SPADE; an efficient algorithm for mining frequent sequences//Machine Learning[M]. Princeton:Princeton University Press,2001 : 30-40.
  • 5Han J, Pei J, Mortazavi-Asl Q, et al. Freespan: Frequent pattern-projected sequential pattern mining[C]. Proceedings of the 2000 International Conference on Knowledge Discovery and Data Mining (KDD'00). Boston: MA, 2000:355-359.
  • 6Masseglia F, Cathala F, Poncelet P. The PsP approach for mining sequential pattems. Principles of Data Mining and Knowledge Discover[M]. Berlin: Springer-Verlag, 1998:176-184.
  • 7Pei J, Han J, Mortazavi-Asl B. H. et al. PrefixSpan: mining sequential patterns efficiently by prefix-projected pattern growth[A]. Proc 2001 Int Conf Data Engineering (ICDE'01)[C]. Heidelberg: IEEE Computer Society Press, 2001 : 15-244.

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部