Towards a social graph approach for modeling risks in big data and internet of things (IoT)

O. Johny, S. Sotiriadis, E. Asimakopoulou, N. Bessis

Research output: Chapter in Book/Report/Conference proceedingConference proceeding (ISBN)peer-review

7 Citations (Scopus)

Abstract

The discovery and integration of big data and Internet of Things (IoTs) highlight new challenges in the area of risks. This work focuses on the analysis of literature review approaches by presenting a study that includes works for resource discovery and data integration, social search engines, ranking techniques, and social graphs in order to provide a cross comparison and a preliminary evaluation study. The approaches are analyzed in order to define theoretical key requirements that could enable the utilization of social graphs towards the discovery and modeling of interconnected entities in big data and IoT scenarios.

Original languageEnglish
Title of host publicationProceedings - 2014 International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2014
EditorsFatos Xhafa, Mario Koeppen, Francesco Palmieri, Vincenzo Loia, Leonard Barolli
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages439-444
Number of pages6
ISBN (Electronic)9781479963867
DOIs
Publication statusPublished - 9 Mar 2015
Event6th International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2014 - Salerno, Italy
Duration: 10 Sep 201412 Sep 2014

Publication series

NameProceedings - 2014 International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2014

Conference

Conference6th International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2014
Country/TerritoryItaly
CitySalerno
Period10/09/1412/09/14

Keywords

  • Big data
  • Data discovery
  • Data integration
  • IoT
  • Risk analysis
  • Social graphs

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