SemaKoDE: Hybrid System for Knowledge Discovery in Sensor-Based Smart Environments

  • Stefan Negru
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7387)

Abstract

This article describes a conceptual hybrid architecture for a knowledge discovery system, able to automatically annotate, reason, classify and operate with sensor data. The adoption of semantic web technologies to enrich sensor and link data represents an adequate methodology that facilitates the processes of reasoning, classification and other types of automation. We discussed a system deployment scenario in the context of e-health.

Keywords

Knowledge Discovery System Sensors Linked Data 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Stefan Negru
    • 1
  1. 1.Faculty of Computer ScienceA. I. Cuza University of IasiRomania

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