Comparative Study Of Data Mining Query Languages

TL;DR

This paper reviews and classifies existing data mining query languages based on their primitives, syntax, and ability to support KDD operations, providing insights into their capabilities and limitations for future research.

Contribution

It offers a comprehensive classification and evaluation of data mining query languages, highlighting their primitives, syntax, and practical applicability to KDD tasks.

Findings

Languages vary in their primitives and syntax support.

Some languages effectively support key KDD operations.

Limitations identified in language capabilities for complex data mining tasks.

Abstract

Since formulation of Inductive Database (IDB) problem, several Data Mining (DM) languages have been proposed, confirming that KDD process could be supported via inductive queries (IQ) answering. This paper reviews the existing DM languages. We are presenting important primitives of the DM language and classifying our languages according to primitives' satisfaction. In addition, we presented languages' syntaxes and tried to apply each one to a database sample to test a set of KDD operations. This study allows us to highlight languages capabilities and limits, which is very useful for future work and perspectives.