Component-based data mining frameworks

Berzal, Fernando; Blanco, Ignacio J.; Cubero, Juan-Carlos; Marín, Nicolás

doi:10.1145/585597.585624

Cited by 23 publications

(14 citation statements)

References 4 publications

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“…and Edwards [49], [68] helped automate test case and test script generation by using their frameworks. -Gallagher and Offutt [69] proposed the use of a finite state machine model to describe component interaction and provide a test method to automate test sequence generation.…”

Section: Literature Surveymentioning

confidence: 99%

A Proposal for New Software Testing Technique for Component Based Software System

Hendradjaya¹

2018

IJEEI

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Section: Literature Surveymentioning

confidence: 99%

A Proposal for New Software Testing Technique for Component Based Software System

Hendradjaya¹

2018

IJEEI

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“…Volatile functionality and implementation details of the data processing algorithms are encapsulated behind stable interfaces. Component-based application frameworks have been proved to suit well for data mining software [1].…”

Section: System Architecturementioning

confidence: 99%

Semi-automatic Maintenance of Regression Models: an Application in the Steel Industry

Juutilainen

Tuovinen

Laurinen

et al. 2011

CIT

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Software applications used in the controlling and planning of production processes commonly make use of predictive statistical models. Changes in the process involve a more or less regular need for updating the prediction models on which the operational software applications are based. The objective of this article is • to provide information which helps to design semiautomatic systems for the maintenance of statistical prediction models and • to describe a proof-of-concept implementation in an industrial application.The system developed processes the production data and provides an easy-to-use interface to construct updated models and introduce them into a software application. The article presents the architecture of the maintenance system, with a description of the algorithms that cause the system's functionality. The system developed was implemented for keeping up-to-date prediction models which are in everyday use in a steel plate mill in the planning of the mechanical properties of steel products. The conclusion of the results is that the semi-automatic approach proposed is competitive with fully automatic and manual approaches. The benefits include good prediction accuracy and decreased workload of the deployment of updated model versions.

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“…Some of the main features of the TMiner component-based data mining framework have already been described elsewhere, (Berzal et al, 2009;Berzal, Blanco, Cubero, & Marín (2002)). …”

Section: The Tminer Data Mining Frameworkmentioning

confidence: 99%

“…Data is gathered from different data sources and data mining algorithms are used in order to build knowledge models (Berzal et al, 2002). Hence TMiner components fall into two main categories: TMinerModels represent the entities data miners work with.…”

Section: Tminer Componentsmentioning

confidence: 99%

TMiner aspects: Crosscutting concerns in the TMiner component-based data mining framework

Berzal

Cortijo

Jiménez

2010

Expert Systems with Applications

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Component-based data mining frameworks

Abstract: OLAP Vs. OLTP in the middle tier.

Cited by 23 publications

References 4 publications

A Proposal for New Software Testing Technique for Component Based Software System

A Proposal for New Software Testing Technique for Component Based Software System

Semi-automatic Maintenance of Regression Models: an Application in the Steel Industry

TMiner aspects: Crosscutting concerns in the TMiner component-based data mining framework

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