DocumentCode :
501329
Title :
Research on Multi-Relational Classification Approaches
Author :
Zhen Peng ; Wu, Lifeng ; Wang, Xiaoju
Author_Institution :
Dept. of Comput., North China Inst. of Sci. & Technol., Beijing, China
Volume :
1
fYear :
2009
fDate :
6-7 June 2009
Firstpage :
51
Lastpage :
54
Abstract :
As an important task of multi-relational data mining, multi-relational classification can directly look for patterns that involve multiple relations from a relational database and have more advantages than propositional data mining approaches. According to the differences in knowledge representation and strategy, the paper researched three kind of multi-relational classification approaches that are ILP based, graph-based and relational database-based classification approaches and discussed each relational classification technology, their characteristics, the comparisons and several challenging researching problems in detail.
Keywords :
data mining; graph theory; inductive logic programming; knowledge representation; pattern classification; relational databases; ILP based classification; graph-based classification; inductive logic programming; knowledge representation; multirelational classification; multirelational data mining; relational database-based classification; Classification tree analysis; Computational intelligence; Data mining; Decision trees; Electronic mail; Knowledge representation; Logic programming; Relational databases; Telecommunication computing; Testing; Inductive Logic Programming (ILP); Multi-relational data mining; graph; multi-relational classification; selection graph; tuple ID propagation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3645-3
Type :
conf
DOI :
10.1109/CINC.2009.166
Filename :
5231577
Link To Document :
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