Author:
Sakai Hiroshi,Shen Kao-Yi,Nakata Michinori, , ,
Abstract
This paper focuses on two Apriori-based rule generators. The first is the rule generator in Prolog and C, and the second is the one in SQL. They are namedApriori in PrologandApriori in SQL, respectively. Each rule generator is based on the Apriori algorithm. However, each rule generator has its own properties. Apriori in Prolog employs the equivalence classes defined by table data sets and follows the framework of rough sets. On the other hand, Apriori in SQL employs a search for rule generation and does not make use of equivalence classes. This paper clarifies the properties of these two rule generators and considers effective applications of each to existing data sets.
Publisher
Fuji Technology Press Ltd.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction
Reference24 articles.
1. R. Agrawal and R. Srikant, “Fast algorithms for mining association rules in large databases,” Proc. VLDB’94, pp. 487-499, 1994.
2. Z. Pawlak, “Rough Sets: Theoretical Aspects of Reasoning About Data,” 1991.
3. A. Skowron and C. Rauszer, “The discernibility matrices and functions in information systems,” Intelligent Decision Support -Handbook of Advances and Applications of the Rough Set Theory, pp. 331-362, 1992.
4. E. Orłowska and Z. Pawlak, “Representation of nondeterministic information,” Theoretical Computer Science, Vol.29, No.1-2, pp. 27-39, 1984.
5. W. Lipski, “On semantic issues connected with incomplete information databases,” ACM Trans. on Database Systems,” Vol.4, No.3, pp. 262-296, 1979.
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献