Use of Object-Oriented Concepts in Databases for Effective Mining

Data mining is a process that uses a variety of data analysis tools to discover knowledge, patterns and relationships in data that may be used to make valid predictions. With the popularity of object-oriented database systems in database applications, it is important to study the data mining methods for object-oriented databases. The traditional Database Management Systems (DBMSs) have limitations when handling complex information and user defined data types which could be addressed by incorporating Object-oriented programming concepts into the existing databases. Classification is a well-established data mining task that has been extensively studied in the fields of statistics, decision theory and machine learning literature. This paper focuses on the design of an object-oriented database, through incorporation of object-oriented programming concepts into existing relational databases. In the design of the database, the object-oriented programming concepts namely inheritance and polymorphism are employed. The design of the object-oriented database is done in such a well equipped manner that the design itself aids in efficient data mining. Our main objective is to reduce the implementation overhead and the memory space required for storage when compared to the traditional databases.