Title : 
A Framework for Object-Oriented Data Mining
         
        
            Author : 
Li, Linna ; Yang, Bingru ; Zhou, Faguo
         
        
            Author_Institution : 
Sch. of Inf. Eng., Univ. of Sci. & Technol. Beijing, Beijing
         
        
        
        
        
        
        
            Abstract : 
Data mining is the discovery of knowledge and useful information from the large amounts of data stored in databases. With the increasing popularity of object-oriented database system in advanced database applications, it is important to study the data mining methods for object-oriented database. This paper proposes that Escher is very suitable for describing knowledge for object-oriented data mining and presents a framework for object-oriented data mining. In this framework, type information of data and semantic information of data model can be used to guide data mining process. A specific data mining task, frequent pattern discovery is investigated under this framework.
         
        
            Keywords : 
data mining; data models; object-oriented databases; data mining; data model; frequent pattern discovery; knowledge discovery; object-oriented database; semantic information; type information; Data engineering; Data mining; Data models; Data structures; Database systems; Fuzzy systems; Knowledge engineering; Logic; Object oriented databases; Relational databases; Data Mining; Higher-Order logical programming; Object-Oriented Database;
         
        
        
        
            Conference_Titel : 
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
         
        
            Conference_Location : 
Shandong
         
        
            Print_ISBN : 
978-0-7695-3305-6
         
        
        
            DOI : 
10.1109/FSKD.2008.298