Relational data mining
From Wikipedia, the free encyclopedia
Relational data mining is the data mining technique for relational databases. Unlike traditional data mining algorithms, which look for patterns in a single table (propositional patterns), relational data mining algorithms look for patterns among multiple tables (relational patterns). For most types of propositional propatterns, there are corresponding relational patterns. For example, there are relational classification rules, relational regression tree, relational association rules, and so on.
The most important theoretical foundation of relational data mining is inductive logic programming.
See also
- Data mining
- Database mining
- Structured data mining
External links
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