Rule Extraction for Blood Donators with Fuzzy Sequential Pattern Mining

Volume 2, Issue 1, pp 37--43 http://dx.doi.org/10.22436/jmcs.002.01.05

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Authors

Fatemeh Zabihi - Industrial Engineering Department, Faculty of Engineering, Shomal University, Amol, Iran Mojtaba Ramezan - Computer Engineering Department, Tarbiat Moallem University, Karaj/Tehran, Iran Mir Mohsen Pedram - Computer Engineering Department, Faculty of Engineering, Tarbiat Moallem University, Karaj/Tehran, Iran Azizollah Memariani - School of Economic Sciences, Tehran, Iran

Abstract

Sequential pattern mining is to discover all sub-sequences that are frequent. The classical sequential pattern mining algorithms do not allow processing of numerical data and require converting these data into a binary representation, which necessarily leads to a loss of information. Fuzzy sets are used to overcome this problem and fuzzy set based algorithms have been proposed to handle numerical data using intervals, particularly fuzzy intervals. In this paper, a fuzzy sequential pattern mining algorithm is applied to mine fuzzy sequential patterns from the Blood Transfusion Service Center data set. It helps to predict future patterns of blood donating behavior.

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Keywords

• Sequence
• Fuzzy Sequential Pattern Mining
• Fuzzy rules.

MSC

•  62L86
•  03E72
•  92C15

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