The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 89-198
Full Name: Wanqing Li
Position: Professor
Age: ON
Sex: Male
Address: Guangming South Street 199,Handan
Country: CHINA
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E-mail address: malihua2004@126.com
Other E-mails: wdongau@yahoo.com.cn
Title of the Paper: data mining based on rough sets in risk decision-making: foundation and application
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Number of paper pages: 11
Abstract: In order to solve the problem of the redundant information to distinguish in the risk decision-making, in this paper, the data mining algorithms based on Rough Sets is studied. And we know the risk decision-making is an important aspect in the management practice. In the risk decision process of a project decision-making, it is necessary to use the algorithm to discover valuable knowledge and make a right decision. In the paper, a data mining method called Rough Sets is introduced in the field. And the algorithmic process of data mining based on Rough Set is studied. According to the Rough Sets theory, firstly, the factors set is established including condition attribute and decision attribute. Secondly, experts qualitatively describe risk factors and establish a decision database, called decision table. Thirdly, the attribute reduction algorithm based on Rough Sets is used to eliminate the redundant risk factor and its value of decision table. Fourthly, the minimu!
m decision rules are abstracted based on data mining technology. Finally, the process of risk decision based on data mining of Rough Sets is analyzed in a case study.
Keywords: Data mining, Rough sets, minimum decision rule, attribute reduction, risk decision, project decision-making
EXTENSION of the file: .rtf
Special (Invited) Session: Data Mining Based on Rough Sets and Its Application in Risk Decision-making
Organizer of the Session: 697-503
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