A kuramoto model based approach to extract and assess influence relations

Marcello Trovati*, Aniello Castiglione, Nik Bessis, Richard Hill

*Corresponding author for this work

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

5 Citations (Scopus)

Abstract

In this paper, we introduce a novel method to extract and assess influence relations between concepts, based on a variation of the Kuramoto Model. The initial evaluation focusing on an unstructured dataset provided by the abstracts and articles freely available from PubMed [7], shows the potential of our approach, as well as suggesting its applicability to a wide selection of multidisciplinary topics.

Original languageEnglish
Title of host publicationComputational Intelligence and Intelligent Systems - 7th International Symposium, ISICA 2015, Revised Selected Papers
EditorsKangshun Li, Jin Li, Yong Liu, Aniello Castiglione
PublisherSpringer Verlag
Pages464-473
Number of pages10
ISBN (Print)9789811003554
DOIs
Publication statusPublished - 19 Jan 2016
Event7th International Symposium on Computational Intelligence and Intelligent Systems, ISICA 2015 - Guangzhou, China
Duration: 21 Nov 201522 Nov 2015

Publication series

NameCommunications in Computer and Information Science
Volume575
ISSN (Print)1865-0929

Conference

Conference7th International Symposium on Computational Intelligence and Intelligent Systems, ISICA 2015
Country/TerritoryChina
CityGuangzhou
Period21/11/1522/11/15

Keywords

  • Data analytics
  • Information extraction
  • Knowledge discovery

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