DocumentCode :
2049764
Title :
Intelligent Data Mining in Autonomous Heterogeneous Distributed Bio Databases
Author :
Shamim, A. ; Shaikh, Maqbool Uddin ; Malik, Saif Ur Rehman
Author_Institution :
Comput. Sci. Dept., COMSAT S Inst. of Inf. Technol., Islamabad, Pakistan
Volume :
1
fYear :
2010
fDate :
19-21 March 2010
Firstpage :
6
Lastpage :
10
Abstract :
A few years ago there is revolutionary change in data mining and bioinformatics. Data mining techniques and tools play important role in field of bioinformatics. It is very useful to use data mining techniques to evaluate and analyze bio-medical data. In this paper authors purpose a frame work for intelligent data mining system for bio databases. This system allows scientist to apply bio data analysis data mining techniques intelligently on bio data as well as their proprietary data. System first extracts the relevant, useful, valid and actionable data from bio databases. Bio databases is often autonomous heterogeneous and distributed in nature. The extracted data is preprocessed. After preprocessing, data mining techniques are applied on preprocessed data, local data as well as proprietary data. Then the mined knowledge is integrated with expert system knowledge to assist researchers and scientists in their research work and crucial decision making process.
Keywords :
bioinformatics; data mining; decision making; distributed databases; expert systems; autonomous heterogeneous distributed bio-databases; bio data analysis; bioinformatics; biomedical data; data preprocessing; decision making process; intelligent data mining; scientist; Application software; Computer applications; Data mining; Deductive databases; Distributed databases; Autonomous heterogeneous distributed bio databases; Data Mining; Expert System; Knowledge base;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Engineering and Applications (ICCEA), 2010 Second International Conference on
Conference_Location :
Bali Island
Print_ISBN :
978-1-4244-6079-3
Electronic_ISBN :
978-1-4244-6080-9
Type :
conf
DOI :
10.1109/ICCEA.2010.9
Filename :
5445878
Link To Document :
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