Relational data mining

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 patterns, there are corresponding relational patterns. For example, there are relational classification rules, relational regression tree, relational association rules, and so on.

There are several approaches to relational data mining. The oldest one is inductive logic programming, in short ILP. Other possible approaches are:

1. Statistical relational learning (SRL)
2. Graph Mining
3. Propositionalization
4. Multi-view learning

See also

• Data mining
• Database mining
• Structured data mining

External links

• Web page for a text book on relational data mining