The following information was submitted:
Transactions: INTERNATIONAL JOURNAL of MATHEMATICS AND COMPUTERS IN SIMULATION
Transactions ID Number: 20-651
Full Name: Hyontai Sug
Position: Associate Professor
Age: ON
Sex: Male
Address: Division of Computer & Information Eng., Dongseo University, Busan, 617-716
Country: KOREA
Tel: 82-51-320-1733
Tel prefix:
Fax: 82-51-327-8955
E-mail address: hyontai@yahoo.com
Other E-mails: shtdaum@hanmail.net
Title of the Paper: Discovery of Multidimensional Association Rules Focusing on Instances in Specific Class
Authors as they appear in the Paper: Hyontai Sug
Email addresses of all the authors: hyontai@yahoo.com
Number of paper pages: 8
Abstract: Conventional association rule finding algorithms as well as multidimensional association rule finding algorithms search association rules based on support, so it is not easy to find association rules of specific class with small support due to computational complexity. In order to overcome the problem of intensive computing time and to avoid the possibility of generating a lot of uninteresting rules, a method that can reduce the intensive computing time and generate smaller number of multidimensional association rules is suggested. By limiting the search for association rules to a specific class in target data set and by selecting instances that have at least one common field value with all instances in the class, the method can reduce the target data set significantly so that computing time can be saved and also smaller number of rules can be generated. Experiments with a real world data set showed a very good result.
Keywords: Class instances, multidimensional association rules, features values
EXTENSION of the file: .pdf
Special (Invited) Session: An Efficient Discovery of Class-Restricted MARs
Organizer of the Session: 650-629
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