DocumentCode :
2521187
Title :
A new attribute reduction algorithm dealing with the incomplete information system
Author :
Zhou, Jin ; Xu, E. ; Li, Yanhong ; Wang, Zhou ; Liu, Zhixu ; Bai, Xiangyu ; Huang, Xuyong ; Di Yang
Author_Institution :
Electron. & Inf. Eng. Coll., Liaoning Univ. of Technol., Jinzhou, China
fYear :
2009
fDate :
10-11 Oct. 2009
Firstpage :
12
Lastpage :
19
Abstract :
To deal with attribute reduction in incomplete information systems, this paper proposed a direct method of attribute relative reduction based on rough set theory. This reduction algorithm gives the concept of tolerance relationship similar matrix via extending equivalence relationship of rough set theory, which is called tolerance relationship. It introduces the generalized decision function to solve the problem of inconsistency in the incomplete information system. This algorithm uses the tolerance relationship similar matrix to calculate the core attributes of incomplete information systems. It applies attribute significance, which this paper puts forward based on attribute frequency in the tolerance relationship similar matrix, as the heuristic knowledge. And it makes use of binsearch heuristic algorithm to calculate the candidate attribute expansion so that it can reduce the expansion times to speed up reduction. Experiment results show that the algorithm is simple and effective.
Keywords :
data mining; data reduction; information systems; matrix algebra; rough set theory; attribute reduction algorithm; attribute relative reduction; generalized decision function; incomplete information system; rough set theory; tolerance relationship similar matrix; Bayesian methods; Educational institutions; Filling; Frequency; Heuristic algorithms; Information systems; Intelligent robots; Intelligent systems; Petrochemicals; Set theory; binsearch heuristic algorithm; generalized decision function; incomplete information system; rough set; tolerance relationship similar matrix;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cyber-Enabled Distributed Computing and Knowledge Discovery, 2009. CyberC '09. International Conference on
Conference_Location :
Zhangijajie
Print_ISBN :
978-1-4244-5218-7
Electronic_ISBN :
978-1-4244-5219-4
Type :
conf
DOI :
10.1109/CYBERC.2009.5342171
Filename :
5342171
Link To Document :
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