DocumentCode :
533230
Title :
Based on rough set of associative rules improve algorithm of data mining
Author :
Zhangkun ; Shaoliangshan
Author_Institution :
Bus. Coll., Liaoning Tech. Univ., Huludao, China
Volume :
11
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
According to information system theory and from the equivalent and support the concept of view, it is easy to find the frequency of collection and confirm the relevant rules of coarse. Under in-depth and systematic research on RS theory and associate rules mining algorithms, This paper make some improvement based on original algorithms. The first and the foremost, this paper proposes an efficient algorithm for counting core and a reduction algorithm of attributes based on discernibility matrix which can handle the knowledge system and make the extraction of decision-rules convenient. Secondly, it put forward a mining model of association rules with decision attributes based on Apriori, AprioriTid and AprioriHybrid algorithms, which also optimize them.
Keywords :
data mining; rough set theory; RS theory; associate rules mining algorithms; data mining; decision rules extraction; discernibility matrix; in-depth research; information system theory; knowledge system; reduction algorithm; rough set; systematic research; Algorithm design and analysis; Association rules; Classification algorithms; Itemsets; Set theory; Asscoiate Rule; Data Mining; Rough Set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5623216
Filename :
5623216
Link To Document :
بازگشت