KDPMEL: A Knowledge Discovery Process Modeling and Enacting Language

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Date

2016

Journal Title

Journal ISSN

Volume Title

Type

Book chapter

Publisher

The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp)

Series Info

Proceedings of the International Conference on Data Mining (DMIN);Pages: 153

Doi

Abstract

Knowledge Discovery in Databases (KDD) is a complex process that is highly interactive and iterative. Managing the process and its underlying resources and interacting activities is a very complex task. Today, KDD projects are typically approached in an unstructured, ad hoc manner due to a lack of formal methods and methodologies for their development. The similarities between KDD processes and software development processes suggest that approaches used to manage the development of software processes, such as process programming and processcentered support environments, are also applicable and in fact advantageous to KDD processes. This paper proposes the Knowledge Discovery Process Modeling and Enacting Language (KDPMEL) that is designed specifically to provide both the syntax and semantics needed to capture and execute KDD processes. KDPMEL combines aspects of both process programming and KDD to represent KDD processes precisely as process programs. Along with KDPMEL, an Integrated Development Environment (IDE) for KDPMEL is proposed to enable and facilitate the development and execution of KDPMEL programs. We illustrate and evaluate KDPMEL by representing and executing illustrative examples of KDD activities and tasks

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MSA Google Scholar

Keywords

October University for University of Data Mining, Knowledge Discovery in Databases (KDD), KDD Process, Process Programming

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