DocumentCode :
3282532
Title :
Classification Rule Mining for Object Oriented Databases: A Brief Review
Author :
Satheesh, Ajita ; Mishra, Durgesh Kumar ; Patel, Ravindra
Author_Institution :
RGPV, UIT, Bhopal, India
fYear :
2009
fDate :
23-25 July 2009
Firstpage :
259
Lastpage :
263
Abstract :
Data mining is the discovery of knowledge and useful information from the data stored in large databases. The classification of large data sets is an important problem in data mining. Most data mining algorithms cannot be applied to complex object databases unless it is converted into a single flat table. Much valuable information especially the linkages between objects could be lost by conversion of such databases into a single table. As object-oriented data models embody rich data structures and semantics in the construction of complex databases, such as complex data objects, class hierarchies, property inheritance and methods, etc. So it is important to extend the area of study from relational database systems to object-oriented database systems and investigate the mechanisms for knowledge discovery in object-oriented databases. This paper presents a brief review of some of the significant researches available in the literature for object-oriented data mining.
Keywords :
data mining; object-oriented databases; reviews; classification rule mining; data mining; data structures; knowledge discovery; large databases; object oriented databases; object-oriented data models; relational database systems; Association rules; Classification tree analysis; Computational intelligence; Data analysis; Data mining; Object oriented databases; Pattern analysis; Predictive models; Relational databases; Road transportation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence, Communication Systems and Networks, 2009. CICSYN '09. First International Conference on
Conference_Location :
Indore
Print_ISBN :
978-0-7695-3743-6
Type :
conf
DOI :
10.1109/CICSYN.2009.60
Filename :
5231924
Link To Document :
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