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Context-Aware Data Mining: Embedding External Data Sources in a Machine Learning Process

  • Oliviu MateiEmail author
  • Teodor Rusu
  • Andrei Bozga
  • Petrica Pop-Sitar
  • Carmen Anton
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10334)

Abstract

The article presents a data mining system capable of predicting the soil moisture using local data, provided by weather stations in real time, as well as context-related, publicly available data from web portals. We have proven that the quality and quantity of context data is very important for improving the accuracy of the predictions, comparing with classical scenario, in which only the local data is used.

Keywords

Context-aware data mining Internet of things Ambience intelligence 

Notes

Acknowledgment

This paper was performed under the frame of the Partnership in priority domains - PNII, developed with the support of MEN-UEFISCDI, project no. PN-II-PT-PCCA-2013-4-0015: Expert System for Risk Monitoring in Agriculture and Adaptation of Conservative Agricultural Technologies to Climate Change.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Oliviu Matei
    • 1
    • 3
    Email author
  • Teodor Rusu
    • 2
  • Andrei Bozga
    • 1
  • Petrica Pop-Sitar
    • 3
  • Carmen Anton
    • 3
  1. 1.Holisun srlBaia MareRomania
  2. 2.University of Agricultural Sciences and Veterinary MedicineCluj-NapocaRomania
  3. 3.Technical University of Cluj-Napoca, North University Centre of Baia MareCluj-NapocaRomania

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