An Efficient Approach for Effectual Mining of Relational Patterns from Multi-Relational Database
Data mining is an extremely challenging and hopeful research topic due to its well-built application potential and the broad accessibility of the massive quantities of data in databases. Still, the rising significance of data mining in practical real world necessitates ever more complicated solutions while data includes of a huge amount of records which may be stored in various tables of a relational database. One of the possible solutions is multi-relational pattern mining, which is a form of data mining operating on data stored in multiple tables. Multi-relational pattern mining is an emerging research area and it has been received considerable attention among the researchers due to its various applications. In the proposed work, we have developed an efficient approach for effectual mining of relational patterns from multi-relational database. Initially, the multi-relational database is represented using a tree-based data structure without changing their relations. A tree pattern mining algorithm is devised and applied on the constructed tree-based data structure for extracting the frequent relational patterns. The experimentation is carried out on customer order database and the comparative results demonstrate that the proposed approach is effective and efficient in mining of relational patterns.
relational pattern multi-relational database data mining tree pattern mining customer order database multi-relational data mining