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Open AccessArticle

Innovative Platform for Designing Hybrid Collaborative & Context-Aware Data Mining Scenarios

1
Electric, Electronic and Computer Engineering Department, Technical University of Cluj-Napoca, North University Center of Baia Mare, 400114 Cluj-Napoca, Romania
2
HOLISUN, 430397 Baia-Mare, Romania
3
Department of Mathematics and Informatics, Technical University of Cluj-Napoca, North University Center of Baia Mare, 400114 Cluj-Napoca, Romania
*
Author to whom correspondence should be addressed.
Mathematics 2020, 8(5), 684; https://doi.org/10.3390/math8050684
Received: 30 March 2020 / Revised: 21 April 2020 / Accepted: 29 April 2020 / Published: 1 May 2020
(This article belongs to the Special Issue Computational Intelligence)
The process of knowledge discovery involves nowadays a major number of techniques. Context-Aware Data Mining (CADM) and Collaborative Data Mining (CDM) are some of the recent ones. the current research proposes a new hybrid and efficient tool to design prediction models called Scenarios Platform-Collaborative & Context-Aware Data Mining (SP-CCADM). Both CADM and CDM approaches are included in the new platform in a flexible manner; SP-CCADM allows the setting and testing of multiple configurable scenarios related to data mining at once. The introduced platform was successfully tested and validated on real life scenarios, providing better results than each standalone technique—CADM and CDM. Nevertheless, SP-CCADM was validated with various machine learning algorithms—k-Nearest Neighbour (k-NN), Deep Learning (DL), Gradient Boosted Trees (GBT) and Decision Trees (DT). SP-CCADM makes a step forward when confronting complex data, properly approaching data contexts and collaboration between data. Numerical experiments and statistics illustrate in detail the potential of the proposed platform. View Full-Text
Keywords: context-aware data mining; collaborative data mining; machine learning context-aware data mining; collaborative data mining; machine learning
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MDPI and ACS Style

Avram, A.; Matei, O.; Pintea, C.; Anton, C. Innovative Platform for Designing Hybrid Collaborative & Context-Aware Data Mining Scenarios. Mathematics 2020, 8, 684. https://doi.org/10.3390/math8050684

AMA Style

Avram A, Matei O, Pintea C, Anton C. Innovative Platform for Designing Hybrid Collaborative & Context-Aware Data Mining Scenarios. Mathematics. 2020; 8(5):684. https://doi.org/10.3390/math8050684

Chicago/Turabian Style

Avram, Anca; Matei, Oliviu; Pintea, Camelia; Anton, Carmen. 2020. "Innovative Platform for Designing Hybrid Collaborative & Context-Aware Data Mining Scenarios" Mathematics 8, no. 5: 684. https://doi.org/10.3390/math8050684

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