Logical Languages for Data Mining

Data mining focuses on the development of methods and algorithms for such tasks as classification, clustering, rule induction, and discovery of associations. In the database field, the view of data mining as advanced querying has recently stimulated much research into the development of data mining query languages. In the field of machine learning, inductive logic programming has broadened its scope toward extending standard data mining tasks from the usual attribute-value setting to a multirelational setting. After a concise description of data mining, the contribution of logic to both fields is discussed. At the end, we indicate the potential use of logic for unifying different existing data mining formalisms.

• Type: Conference
• Year: 2003
• Where: DAGSTUHL
• Authors: Fosca Giannotti, Giuseppe Manco, Jef Wijsen
• Keywords: DAGSTUHL 2003, DAGSTUHL 2007, Data Mining, Data Mining Query, Data Mining Tasks