DocumentCode :
2329053
Title :
Association rules mining on concept lattice using domain knowledge
Author :
Wang, De-Xing ; Hu, Xue-Gang ; Liu, Xiao-Ping ; Wang, Hao
Author_Institution :
Dept. of Comput. Sci. & Technol., Hefei Univ. of Technol., China
Volume :
4
fYear :
2005
fDate :
18-21 Aug. 2005
Firstpage :
2151
Abstract :
Large databases make computation of knowledge discovery more and more expensive, then it is proved counter-evidently that domain knowledge hidden in the database, can often guide and restrict the search for interesting knowledge, play more roles in guiding knowledge discovery in databases. While concept lattice represents knowledge on the Hass diagram with the relationships between entities and attributes, then the knowledge can be shown with hierarchical structure on the Hass diagram, thus it is properly applied to the description of association rules mining in databases. In the paper, we discuss how to use domain knowledge to guide association rules mining on concept lattice, association rules mining on which can be shown that it represents the rules more visual, vivid and concise, if using domain knowledge, we can reduce the search space, avoid blocking unexpected discoveries, so knowledge discovery can be improved effectively.
Keywords :
data mining; very large databases; Hass diagram; association rules mining; concept lattice; domain knowledge; knowledge discovery; search space; Access control; Association rules; Computer science; Data analysis; Data mining; Dictionaries; Lattices; Statistics; Testing; Visual databases; Data mining; association rule; concept lattice; domain knowledge;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
Type :
conf
DOI :
10.1109/ICMLC.2005.1527301
Filename :
1527301
Link To Document :
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