Classification method for interval valued relational database

THUIR > College of Engineering > Department of Computer Science and Information > Conference Papers > Item 310901/22241

Please use this identifier to cite or link to this item: http://140.128.103.80:8080/handle/310901/22241

Title:	Classification method for interval valued relational database
Authors:	Xu, B., Lu, J., Chu, W.C., Yang, H.
Contributors:	Dept. of Computer Science, Tunghai University,
Keywords:	Algorithms;Boolean algebra;Classification (of information);Data mining;Fuzzy sets;Knowledge based systems
Date:	2003-06-23
Issue Date:	2013-05-15T09:13:43Z (UTC)
Publisher:	Las Vegas, NV; United States
Abstract:	Classification and association rules are important research issues and focuses of data mining technology. A classification method of association rules with linguistic variables, which fits for the interval valued relational database, is presented. In this classification method, values of the record in each attribute are partitioned into several linguistic variables by the fuzzy c-medoids algorithm. Then, Apriori algorithm is improved for mining interesting association rules with linguistic variables in the interval valued relational database. Last, we use these interesting association rules with linguistic variables to build classification system. The classification method is implemented on a constructed interval valued relational database. The experiment results show that the classification method has fine accuracy.
Relation:	Proceedings of the International Conference on Information and Knowledge Engineering 2 , pp. 566-570
Appears in Collections:	[Department of Computer Science and Information ] Conference Papers

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