PCSE-KDD: A Process-Centered Support Environment for the Knowledge Discovery Processes

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dc.AffiliationOctober University for modern sciences and Arts (MSA)
dc.contributor.authorA. Mansour, Hesham
dc.date.accessioned2020-02-20T07:05:25Z
dc.date.available2020-02-20T07:05:25Z
dc.date.issued2016
dc.descriptionMSA Google Scholaren_US
dc.description.abstractCurrent support for Knowledge Discovery in Databases (KDD) is provided only for fragments of the process, a particular KDD process model, or most recently certain process aspects. The support needed for a KDD process varies greatly based on the specifications of the concrete KDD process, and cannot be based purely on a generic process model. There is a need for a more comprehensive support approach that can cover the entire process, target concrete process specifications, and include various aspects of the process. KDD processes are similar to software processes and they can benefit from advancement of software engineering and process technology to facilitate their development, support their execution, and ultimately improve their effectiveness, utilization, and outcomes. This paper proposes the Process-Centered Support Environment for KDD (PCSE-KDD) processes that is based on explicitly representing these processes as process programs that can be developed, managed, and enacted by the environment. This approach has been successfully used to provide support for developing software processes and we propose to transplant this approach into the KDD field. With the proposed approach, KDD processes can be flexibly captured at different levels of details in a clear, precise, and explicit way that can enable reasoning about the process, insuring its correct execution, and supporting its performanceen_US
dc.description.sponsorshipThe Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp)en_US
dc.description.urihttps://www.scimagojr.com/journalsearch.php?q=17200154716&tip=sid&clean=0
dc.identifier.citation[1] Mansour, H. A., Duchamp, D., and Krapp, C.-A. A LanguageBased and Process-Oriented Approach for Supporting the Knowledge Discovery Processes. In Proceedings of the 11th International Conference on Data Mining (DMIN’15) (pp. 107-115), July 2015. [2] Mansour, H. A. (in press). KDPMEL: A Knowledge Discovery Process Modeling and Enacting Language. The 12th International Conference on Data Mining (DMIN’16), July 2016. [3] Mansour, H. A. A Process-Centered Environment for Modeling, Enacting, and Managing the Knowledge Discovery Processes. PhD dissertation, Stevens Institute of Technology, Hoboken, N. J., 2015. [4] David Jensen et al. Coordinating Agent Activities in Knowledge Discovery Processes, Department of Computer Science, University of Massachusetts Amherst, 1999. [5] The JavaCC Framework. URL: https://javacc.dev.java.net/ [6] The SQL-92 Standard. URL: http://www.contrib.andrew.cmu.edu/~shadow/sql/sql1992.txt. [7] L. Kurgan and P. Musilek. A Survey of Knowledge Discovery and Data Mining Process Models. Knowledge Engineering Review, 21(1), pp. 1-24, 2006. [8] Marban, O. et al. An Engineering Approach to Data Mining Projects. Intelligent Data Engineering and Automated Learning – IDEAL 2007, LNCS 4881, pp. 578-588, 2007. [9] Marban, O. et al. Toward data mining engineering: A software engineering approach. Information Systems 34 (1), 2009. [10] Pohl, K. et al. PRIME-Toward Process-Integrated Modeling Environments. ACM Transactions on Software Engineering and Methodology, Vol. 8, No. 4, October 1999, Pages 343-410. [11] The Eclipse Modeling Framework (EMF). URL: http://www.eclipse.org/modeling/emf/ [12] The Eclipse Graphical Modeling Framework (GMF). URL: http://wiki.eclipse.org/Graphical_Modeling_Framework/ [13] The Graphical Editing Framework (GEF). URL: http://www.eclipse.org/gef/ [14] University of Waikato, New Zealand. Weka 3: Data Mining Software in Java. URL: http://www.cs.waikato.ac.nz/ml/weka/ [15] Open Source, The State Machine Compiler (SMC) Framework, URL: http://smc.sourceforge.net/ [16] The JGoodies Framework. URL: https://jgoodies.dev.java.net/ [17] The xText Language Development Framework. URL: http://www.eclipse.org/Xtext/ [18] Rudiger Wirth et al. Towards Process-Oriented Tool Support for Knowledge Discovery in Databases. DaimlerChrysler Research & Technology, 1997. [19] Cinara Ghedini and Karin Becker. A documentation model for the KDD application management support. Faculdade de Informatica, PUCRS 2000. [20] Osterweil, L.J. Software Processes are Software Too. In Proceedings of the Ninth International Conference on Software Engineering, pp 2-14, 1987. [21] B.C. Warboys et al. Collaboration and Composition: Issues for a Second Generation Process Language. 1999. [22] Vincenzo Ambriola et al. Assessing Process-centered Software Engineering Environments. Universita di Pisa, NTH-Trondheim, Politecnico di Milano, 1996. [23] Padhraic Smyth. Breaking Out of the Black-Box: Research Challenges in Data Mining. The 2001 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, 2001. [24] Fayyad U. M., Piatetsky-Shapiro, G., and Uthurusamy, R. Summary from the KDD-03 Panel – Data Mining: The Next 10 Years. The 9th International Conference on Data Mining and Knowledge Discovery: KDD-03, August 27, 2003. [25] J. Segovia. Definition and Instantiation of an Integrated Data Mining Process. Jornadas de Seguimiento de Proyectos, 2007. [26] Using Perspectives in the Eclipse UI. URL: https://www.eclipse.org/articles/usingperspectives/PerspectiveArticle.html [27] The JGraph Framework. URL: http://www.jgraph.com/jgraph.htmlen_US
dc.identifier.isbn1-60132-431-6
dc.identifier.urihttps://t.ly/rx5rZ
dc.language.isoenen_US
dc.publisherThe Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp)en_US
dc.relation.ispartofseriesProceedings of the International Conference on Data Mining (DMIN);Pages: 168
dc.subjectOctober University for University of KDD Process, Process Programming, ProcessCentered Support Environmentsen_US
dc.titlePCSE-KDD: A Process-Centered Support Environment for the Knowledge Discovery Processesen_US
dc.typeBook chapteren_US

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