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PrefixSpan算法在多维序列模式挖掘中的应用 被引量：3

Application of Algorithm PrefixSpan in Multi-dimensional Sequential Pattern Mining
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摘要 多维序列模式挖掘是在序列模式挖掘的基础上发展起来的,文章阐述了有关概念,介绍了两种序列模式挖掘算法:GSP算法和PrefixSpan算法,在对两类算法进行比较分析的基础上形成了挖掘多维序列模式的UniSeq算法、Dim-Seq算法和Seq-Dim算法。针对不同维度的模式,各种算法特点不同。 Multi-dimensional sequential pattern mining is based on and developed from sequential pattern mining. It firstly presents some related conceptions,then introduces two kinds of sequential pattern mining algorithms: GSP and PrefixSpan,then forms algorithm UniSeq, Dim-Seq and Seq-Dim on the basis of analysis and comparison of algorithm GSP and PrefixSpan. Each algorithm has different character aiming at different-dimension pattern.
作者 栾东庆 徐素琴
机构地区 首都经济贸易大学信息学院 上海荣联通信科技有限公司研发部
出处 《微机发展》 2003年第8期83-86,89,共5页 Microcomputer Development
关键词 数据挖掘 PREFIXSPAN算法 多维序列模式挖掘 序列数据库 data mining sequential pattern support threshold projected database
分类号 TP311.13 [自动化与计算机技术—计算机软件与理论]
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参考文献4

  • 1Srikant R,Agrawal R. Mining quantitative association rules in large relational tables[A]. In Proc. 1996 ACM - SIGMOD INT. Conf. Management of Data(SIGMOD' 96 ) [ C ]. Montreal, Canada: [s. n. ], 1996.
  • 2Pei J,Han J,Mortazavi- Asl B, et al. PrefixSpan: Mining sequential patterns efficiently by prefix- projected pattern growth[A]. In Proc. 9001 Int. Conf. Data Engineering(ICDE'01) [C], Heidelberg,Germany: [s. n. ] ,2001.
  • 3Beyer K,Ramakrishnan R. Bottom- up computation sparse and iceberg cubes[A]. In Proc. 1999 ACM - SIGMOD Int.Cord.Management of Data (SIGMOD99') [C]. Philadelphia:[ s. n. ], PA, 1999. 359 - 370.
  • 4Pinto H, Han J, Pei J, et al. Multi - dimensional Sequential Pattern Mining[ A]. In Proc. 10th ACM International Conference on Information and Knowledge Mansgement(CIKM' 01)[C]. Atlanta,Georgia: [s. n. ] ,2001.

同被引文献13

  • 1祝效普,梁洪峻.序列模式挖掘在网络业务流分析中的应用[J].计算机应用,2004,24(8):66-68. 被引量：3
  • 2刘晓东.数据挖掘在图书馆工作中的应用[J].情报杂志,2005,24(8):63-65. 被引量：29
  • 3Pei J,Han J,Mortazavi-Asl B.et a1.PrefixSpan:Mining sequential patterns efficiently by prefix-projected pattern growth[C].In Proceedings of 17th International Conference on Data Engineering,April 2001,215~224
  • 4Pinto H.Hart J,Pci J.Wang K,Chen Q,Dayal U.Multi.dimensional sequential pattern mining[C].In Proceedings of 10th International Conference on Information and knowledge managemen,October 2001,81-88
  • 5Han J.Dong G and Yin Y.Efficient mining of panel periodic patterns in time series database[C].In Proceedings of International Conference Data Engineering(ICDE99),March 1999,105～115
  • 6R.Agrawal, R.Srikant. Mining Sequential Pattems [C]. In: Proceeding of the 11st International Conference on Data Engineering.TaiPei, 1995: 3-14.
  • 7R.Agrawal, R.strkant. Fast Algorithms for Minig Association Rules [C]. In: Proceeding of the 20th International Conference on Very Large Databases. Santiage, Chile, September, 1994: 487-499.
  • 8J. Pei, J. Han, B. Mortazavi-Asl, H. Pinto, Q. Chen, U. Dayal, and M.-C. Hsu. PrefixSpan: Mining sequential patterns efficiently by prefix-projected pattern growth [C], In Proceeding of 2001 International Conference on Data Engineering (ICD'01). Heidelberg, Germany, April, 2001: 215-224.
  • 9J.Pei, J. Hart, B.Mortazavi-Asl, H. PintoQ, Chen U. Dayal and M-C.Hsu. PrefixSPan: Mining sequential Pattems efficiently by Prefix-Projected Pattern growth[J]. IEEE Transactions on Knowledge and Data Engineering,2004, 16(11): 1424-1440.
  • 10Pei J, Han J, Mortazavi-Asl B, et al. PrefixSpan: Mining se- quential patterns efficiently by prefix-projected pattern growth. In Proceedings of 17th International Conference on Data Engineering, April 2001, 215-224.

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微机发展
2003年 第8期

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