KDDML: A middleware language and system for knowledge discovery in databases

• Published in: Data & knowledge engineering Vol. 57; no. 2; pp. 179 - 220
• Main Authors: Romei, Andrea, Ruggieri, Salvatore, Turini, Franco
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.05.2006
• Subjects: Data mining; Knowledge discovery in databases; Query languages; Knowledge discovery in databases; Data mining; Query languages
• ISSN: 0169-023X; 1872-6933
• DOI: 10.1016/j.datak.2005.04.007

KDDML (KDD Markup Language) is a middleware language and system designed to support the development of final applications or higher level systems which deploy a mixture of data access, data preprocessing, extraction and deployment of data mining models. We present our three-years’ experience in the development of KDDML. The design principles are motivated by requirements derived from recurring patterns in the KDD process. The KDDML language is XML-based, both for query syntax and data/model representation. A KDDML query is an XML-document where XML tags correspond to operations on data/models, XML attributes correspond to parameters of those operations and XML sub-elements define arguments passed to the operators. We present the operators for data access and preprocessing, model extraction and deployment, and control flow ones. The core of the KDDML system is a KDDML language interpreter with modularity and extensibility requirements as the main goals. Additional data sources, and preprocessing and mining algorithms can be easily plugged in the system.