Relational data mining

<p>Relational data mining is the <a href="/facts/Data_mining/AH53q5ac">data mining</a> 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 <a href="/facts/Classification_rule/n9IbC4Xo">classification rules</a> (relational classification), relational <a href="/facts/Decision_tree_learning/LbPMAwdI">regression tree</a>, and relational <a href="/facts/Association_rule/oX6w9Kux">association rules</a>.
</p><p>There are several approaches to relational data mining:
</p>
<ol><li><a href="/facts/Inductive_logic_programming/gKc9Nxq4">Inductive Logic Programming</a> (ILP)</li>
<li><a href="/facts/Statistical_relational_learning/tFA87qG1">Statistical Relational Learning</a> (SRL)</li>
<li><a href="/facts/Structure_mining/wTYpHwGA">Graph Mining</a></li>
<li>Propositionalization</li>
<li>Multi-view learning</li></ol>

Relational data mining open-in-new

Relational data mining