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基于三维坐标的关联规则可视化新技术 被引量：4

New Visualization Technique for Association Rules Based on Three-dimensional Coordinate
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摘要 关联规则可视化技术中普遍存在界面紊乱、产生歧义等问题。该文提出一种新的关联规则可视化方法ARVMiner,利用三维坐标可视化技术改进现有可视化技术的不足。采用Java 3D可视化技术实现了基于ARVMiner的关联规则可视化系统原型。实验表明,该系统能够有效、有序地显示大量多种关系的关联规则,用户可以根据给定的约束条件进行有选择的挖掘。 There are many common problems such as confusion and ambiguity in the visualization results. A new novel method ARVMiner for visualizing association rules is introduced, which uses three-dimensional coordinate to improve those existed visualization techniques. A system for visualizing association rules based on ARVMiner is implemented with Java 3D. The system is not only efficiently and orderly visualizes all kinds of association rules, but also filters the mined results by constraint condition.
作者 易先卉 彭黎
机构地区 湖南大学软件学院
出处 《计算机工程》 CAS CSCD 北大核心 2008年第22期57-59,共3页 Computer Engineering
关键词 关联规则 可视化 数据挖掘 association rule visualization data mining
分类号 TP311.52 [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10

  • 1Wong Pak Chung, Whitney P, Thomas J. Visualizing Association Rules for Text Mining[C]//Proceedings of the 1999 IEEE Symposium on Information Visualization. Richland, USA: [s. n.], 1999: 120-123.
  • 2Hetzler B, Harris W M, Havre S, et al. Visualizing the Full Spectrum of Document Relationships[C]//Proceedings of the 5th Int'l Conf. of Society for Knowledge Organization. Wurzburg, France: Verlag, 1998: 168-175.
  • 3Li Yang. Visualizing Frequent Itemsets, Association Rules, and Sequential Patterns in Parallel Coordinates[C]//Proceedings of Int'l Conf. on Computational Science and Its Applications. Montreal, Canada:[s. n.], 2003: 21-30.
  • 4Li Yang. Pruning and Visualizing Generalized Association Rules in Parallel Coordinates[J]. IEEE Transactions on Knowledge and Data Engineering, 2005, 17(1): 60-70.
  • 5吉根林,韦素云,曲维光.基于平行坐标的关联规则可视化新技术[J].计算机工程,2005,31(24):87-89. 被引量：5
  • 6Han Jiaochan, Cercone N. RuleViz: A Model for Visualizing Knowledge Discovery Process[C]//Proceedings of KDD'00. Boston, USA: [s. n.], 2000: 244-253.
  • 7Agrawal R, Imielinski T, Swami A. Mining Association Rules Between Sets of Items in Large Databases[C]//Proceedings of the ACM SIGMOD Int'l Conf. on Management of Data. Washington, USA: [s. n.], 1993: 207-216.
  • 8Agrawal R, Srikant R. Fast Algorithms for Mining Association Rules[C]//Proceedings of 1994 Int'l Conf. on Very Large Data Bases. Santiago, Chile: [s. n.], 1994: 487-499.
  • 9Han Jiawei, Pei Jian, Yin Yiwen. Mining Frequent Patterns Without Candidate Generation[C]//Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data. Dallas, USA: [s. n.], 2000: 1-12.
  • 10Cristofor D, Cristofor L, Simovici D. Galois Connection and Data Mining[J]. Journal of Universal Computer Science, 2000, 6(1): 60-73.

二级参考文献8

  • 1Wong P C, Whitney P, Thomas J. Visualizing Association Rules for Text Mining[C]. In: Proc. of the 1999 IEEE Symposium on Information Visualization, Richland, USA, 1999:120-123.
  • 2Ong K H, Ong K L, Ng W K, et al. Crystalclear: Active Visualization of Association Rules[C]. In: International Workshop on Active Mining, in Conjunction with IEEE International Conference on Data Mining, Maebashi, Japan, 2002-12.
  • 3Hofmann H, Siebes A, Wilhelm A. Visualizing Association Rules with Interactive Mosaic Plots[C]. In: Proc. of 6th ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining, Boston, USA,2000-08:227-235.
  • 4Yang L. Visualizing Frequent Itemsets, Association Rules, and Sequential Patterns in Parallel Coordinates[C]. In: Proc. of Int'l Conf.Computational Science and Its Applications, Montreal, Canada,2003-05:21-30.
  • 5Yang L. Pruning and Visualizing Generalized Association Rules in Parallel Coordinates[J]. IEEE Transactions on Knowledge and Data Engineering, 2005, 17(1): 60-70.
  • 6Techapichetvanich K, Datta A. VisAR: A New Technique for Visualizing Mined Association Rules[C]. In: Proc. of 1st Int'l Conf.Advanced Data Mining and Applications, 2005:88-95.
  • 7Hetzler B, Harris W M, Havre S, et al. Visualizing the Full Spectrum of Document Relationships[C]. In: Proc. of 5th Int'l Conf. Society for Knowledge Organization. Wurzburg, Verlag, 1998:168-175.
  • 8Techapichetvanich K, Datta A. Visual Mining of Market Basket Association Rules[C]. In: Proc. of 2004 Int'l Conf. Computational Science and Its Applications, Assisi, Italy, 2004-05:479-488.

共引文献4

同被引文献48

引证文献4

二级引证文献6

计算机工程
2008年 第22期

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