DocumentCode :
1925085
Title :
Parameterization reduction using soft set theory for better decision making
Author :
Kumar, D. Arun ; Rengasamy, R.
Author_Institution :
Dept. of Comput. Sci., Gov. Arts Coll., Tiruchirapalli, India
fYear :
2013
fDate :
21-22 Feb. 2013
Firstpage :
365
Lastpage :
367
Abstract :
Information science plays a vital role in each and every field of science and technology, but it is facing several difficulties to handle the data and information, a main problem is data uncertainty, several theories are dealing with uncertainty, soft set theory also do vital role to handle this uncertainty problem. This paper analysed soft set reduction and how a sample dataset is converted into binary valued information system, and also analysed how binary valued information can be used to reduce dimension of data to take better decisions.
Keywords :
decision making; information systems; set theory; binary valued information system; data dimension reduction; data uncertainty problem; decision making; information science; parameterization reduction; soft set theory; Approximation methods; Decision making; Information systems; Pattern recognition; Set theory; Uncertainty; Information system; parameterization; reduction; soft set; uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, Informatics and Mobile Engineering (PRIME), 2013 International Conference on
Conference_Location :
Salem
Print_ISBN :
978-1-4673-5843-9
Type :
conf
DOI :
10.1109/ICPRIME.2013.6496502
Filename :
6496502
Link To Document :
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