Aviz: A visualization system for discovering numeric association rules

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1805, Issue , 2000, Pages 269-280

  Han, Jianchao ^a   Cercone, Nick ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Association rules; Data mining; Data visualization; KDD

Indexed keywords

ASSOCIATION RULES; DATA MINING; POPULATION STATISTICS; VISUALIZATION;

BIN PACKING; CENSUS DATA; LARGE DATASETS; NUMERICAL ATTRIBUTES; VISUALIZATION SYSTEM;

DATA VISUALIZATION;

EID: 84942753211     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45571-x_33     Document Type: Conference Paper

References (13)

1. R. Agrawal, R. Srikant, Fast algorithm for mining association rules in large databases, Proc. of the 20th International Conference on VLDB, pp.487-499, Sept. 1994.
2. Y. Cai, N. Cercone, J. Han, Attribute Oriented Induction in Relational Databases, in Knowledge Discovery in Databases ed. by Gregory Piatetsky-Shapiro and William J. Prawley, pp.213-228, 1991.
3. M. Derthick, J. Kolojejchick, S. F. Roth, An Interactive Visualization Environment for Data Exploration, KDD-97, pp.2-9, 1997.
4. T. Fukuda, Y. Morimoto, S. Morishita, T. Tokuyama, Data Mining Using Two-Dimensional Optimized Association Rules: Scheme, Algorithms, and Visualization, Proc of the ACM SIGMOD International Conference on Management of Data, pp. 13-24, 1996.
5. R. Groth, Data Mining: A Haxids-on Approach for Business Professionals, Prentice Hall PTR, 1998.
6. J. Han, N. Cercone, DVIZ: A System for Visualizing Data Mining, Proc of the 3rd Pacific-Asia Knowledge Discovery in Databases, pp. 390-399, 1999.
7. D. A. Keim, H. P. Kriegel, Visualization Techniques for Mining Large Databases: A Comparison, Transactions on Knowledge and Data Engineering, Dec.,1996.
8. D. Keim, Vizual Data Mining, Proceedings of International Conference on Very Large Data Bases, 1997.
9. J. B. Kennedy, K. J. Mitchell, P. J. Barchay, A framework for information visualization, SIGMORD Record, VoL 25, No.4, Dec, 1996.
10. B. Liu, W. Hsu, K. Wang, S. Chen, Visually Aided Exploration of Interesting Association Rules, Proc of the 3rd Pacific-Asia Knowledge Discovery in Databases, pp. 380-389, 1999.
11. R. J. Miller, Y. Yang, Association Rules over Interval Data, Proc of the ACM SIGMOD International Conference on Management of Data, pp. 452-461, 1997.
12. G. Piatetsky-Shapiro, Discovery, Analysis, and Presentation of Strong Rules, in Knowledge Discovery in Databases ed. by Gregory Piatetsky-Shapiro and William J. Prawley, pp.229-260, 1991.
13. R. Srikant, R. Agrawal, Mining Quantitative Association Rules in Large Relational Tables, Proc of the ACM SIGMOD International Conference on Management of Data, pp.1-12, 1996.