DocumentCode :
3265708
Title :
Optimization of knowledge discovery process using domain knowledge
Author :
Owrang, M. Mehdi
Author_Institution :
Dept. of Comput. Sci. & Inf. Syst., American Univ., Washington, DC, USA
fYear :
35765
fDate :
8-10 Dec1997
Firstpage :
428
Lastpage :
433
Abstract :
Modern database technologies process large volumes of data to discover new knowledge. Some large databases make discovery computationally expensive. Additional knowledge, known as domain or background knowledge, can often guide and restrict the search for interesting knowledge. We discuss mechanisms by which domain knowledge can be used effectively in discovering knowledge from databases. In particular, we look at the use of domain knowledge to reduce the search as well as to optimize the hypotheses which represent the interesting knowledge to be discovered
Keywords :
database theory; deductive databases; knowledge acquisition; optimisation; search problems; very large databases; background knowledge; computationally expensive; deductive database; domain knowledge; knowledge discovery; knowledge discovery process optimization; large data volumes; large databases; search; Computer science; Data analysis; Data mining; Databases; Information systems; Packaging; Pattern recognition; Quality control; Rough sets; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Systems, 1997. IIS '97. Proceedings
Conference_Location :
Grand Bahama Island
Print_ISBN :
0-8186-8218-3
Type :
conf
DOI :
10.1109/IIS.1997.645328
Filename :
645328
Link To Document :
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