An analytical tool to map big data to networks with reduced topologies

M. Trovati, E. Asimakopoulou, N. Bessis

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

8 Citations (Scopus)

Abstract

The topological and dynamical properties of real-world networks have attracted extensive research from a variety of multi-disciplinary fields. They, in fact, model typically big datasets which pose interesting challenges, due to their intrinsic size and complex interactions, as well as the dependencies between their different sub-parts. Therefore, defining networks based on such properties, is unlikely to produce usable information due to their complexity and the data inconsistencies which they typically contain. In this paper, we discuss the evaluation of a method as part of ongoing research which aims to mine data to assess whether their associated networks exhibit properties comparable to well-known structures, namely scale-free, small world and random networks. For this, we will use a large dataset containing information on the seismologic activity recorded by the European-Mediterranean Seismological Centre. We will show that it provides an accurate, agile, and scalable tool to extract useful information. This further motivates our effort to produce a big data analytics tool which will focus on obtaining in-depth intelligence from both structured and unstructured big datasets. This will ultimately lead to a better understanding and prediction of the properties of the system(s) they model.

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.
Pages411-414
Number of pages4
ISBN (Electronic)9781479963867
ISBN (Print)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

  • Data analytics
  • Information extraction
  • Knowledge discovery
  • Networks
  • Seismological data
  • Social graphs

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