A Survey of the State of the Art in Data Mining and Integration Query Languages

TL;DR

This survey evaluates various Data-Mining and Integration query languages by analyzing their strengths and weaknesses using a systematic scoring system, aiming to guide future research and practical application.

Contribution

It introduces a set of properties and a scoring system for systematic evaluation of DMI query languages, providing a comprehensive comparison of existing languages.

Findings

Identified strengths and weaknesses of surveyed languages

Developed a scoring system for property support

Provided insights for future language development

Abstract

The major aim of this survey is to identify the strengths and weaknesses of a representative set of Data-Mining and Integration (DMI) query languages. We describe a set of properties of DMI-related languages that we use for a systematic evaluation of these languages. In addition, we introduce a scoring system that we use to quantify our opinion on how well a DMI-related language supports a property. The languages surveyed in this paper include: DMQL, MineSQL, MSQL, M2MQL, dmFSQL, OLEDB for DM, MINE RULE, and Oracle Data Mining. This survey may help researchers to propose a DMI language that is beyond the state-of-the-art, or it may help practitioners to select an existing language that fits well a purpose.