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
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