DocumentCode :
2293189
Title :
Investigation and application of extension data mining based on rough set
Author :
Tang, Zhi-Hang ; Yang, Bao-An
Author_Institution :
Sch. of Comput. & Commun., Hunan Inst. of Eng., Xiangtan, China
fYear :
2009
fDate :
14-16 Sept. 2009
Firstpage :
112
Lastpage :
118
Abstract :
In the database of information system, usually there are some attributes which are unimportant to the decision attribute, and some records that disturb the decision making. In this paper, reducing the condition attributes based on the matter-element theory and rough set method, calculating the importance to the decision attribute for each condition attribute after reduction, and data mining the relevant rules based on the reduced attributes, extension relevant function is used to depict quality of data gather in data mining. Finally, how to tap new customers and how to recommend an appropriate brand to new customers, Research result indicates that extension data mining can provide effective decide support for the decision-making of enterprise.
Keywords :
data mining; decision making; rough set theory; condition attribute reduction; customer service; database; decision attribute; decision making; extension data mining; extension relevant function; information system; matter-element theory; rough set method; Conference management; Data analysis; Data engineering; Data mining; Databases; Decision making; Engineering management; Information systems; Machine learning; Rough sets; attributes reduction; extension data mining; matter-element; rough set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Management Science and Engineering, 2009. ICMSE 2009. International Conference on
Conference_Location :
Moscow
Print_ISBN :
978-1-4244-3970-6
Electronic_ISBN :
978-1-4244-3971-3
Type :
conf
DOI :
10.1109/ICMSE.2009.5318868
Filename :
5318868
Link To Document :
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