A Kuramoto Model Based Approach to Extract and Assess Influence Relations

Marcello Trovati, Aniello Castiglione, Nik Bessis, Richard Hill

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 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
Subtitle of host publication7th International Symposium, ISICA 2015, Guangzhou, China, November 21-22, 2015, Revised Selected Papers
EditorsKangshun Li, Jin Li, Yong Liu, Aniello Castiglione
PublisherSpringer Verlag
Pages464-473
Number of pages10
ISBN (Electronic)9789811003561
ISBN (Print)9789811003554
DOIs
Publication statusPublished - 19 Jan 2016
Externally publishedYes
Event7th International Symposium on Computational Intelligence and Intelligent Systems - Guangzhou, China
Duration: 21 Nov 201522 Nov 2015
Conference number: 7

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer
Volume575
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference7th International Symposium on Computational Intelligence and Intelligent Systems
Abbreviated titleISICA 2015
CountryChina
CityGuangzhou
Period21/11/1522/11/15

Fingerprint

Kuramoto Model
Model-based
Evaluation
Concepts
Influence

Cite this

Trovati, M., Castiglione, A., Bessis, N., & Hill, R. (2016). A Kuramoto Model Based Approach to Extract and Assess Influence Relations. In K. Li, J. Li, Y. Liu, & A. Castiglione (Eds.), Computational Intelligence and Intelligent Systems: 7th International Symposium, ISICA 2015, Guangzhou, China, November 21-22, 2015, Revised Selected Papers (pp. 464-473). (Communications in Computer and Information Science; Vol. 575). Springer Verlag. https://doi.org/10.1007/978-981-10-0356-1_49
Trovati, Marcello ; Castiglione, Aniello ; Bessis, Nik ; Hill, Richard. / A Kuramoto Model Based Approach to Extract and Assess Influence Relations. Computational Intelligence and Intelligent Systems: 7th International Symposium, ISICA 2015, Guangzhou, China, November 21-22, 2015, Revised Selected Papers. editor / Kangshun Li ; Jin Li ; Yong Liu ; Aniello Castiglione. Springer Verlag, 2016. pp. 464-473 (Communications in Computer and Information Science).
@inproceedings{271cc3cf072e49e686de5db048c4d81e,
title = "A Kuramoto Model Based Approach to Extract and Assess Influence Relations",
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.",
keywords = "Data analytics, Information extraction, Knowledge discovery",
author = "Marcello Trovati and Aniello Castiglione and Nik Bessis and Richard Hill",
year = "2016",
month = "1",
day = "19",
doi = "10.1007/978-981-10-0356-1_49",
language = "English",
isbn = "9789811003554",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "464--473",
editor = "Kangshun Li and Jin Li and Yong Liu and Aniello Castiglione",
booktitle = "Computational Intelligence and Intelligent Systems",

}

Trovati, M, Castiglione, A, Bessis, N & Hill, R 2016, A Kuramoto Model Based Approach to Extract and Assess Influence Relations. in K Li, J Li, Y Liu & A Castiglione (eds), Computational Intelligence and Intelligent Systems: 7th International Symposium, ISICA 2015, Guangzhou, China, November 21-22, 2015, Revised Selected Papers. Communications in Computer and Information Science, vol. 575, Springer Verlag, pp. 464-473, 7th International Symposium on Computational Intelligence and Intelligent Systems , Guangzhou, China, 21/11/15. https://doi.org/10.1007/978-981-10-0356-1_49

A Kuramoto Model Based Approach to Extract and Assess Influence Relations. / Trovati, Marcello; Castiglione, Aniello; Bessis, Nik; Hill, Richard.

Computational Intelligence and Intelligent Systems: 7th International Symposium, ISICA 2015, Guangzhou, China, November 21-22, 2015, Revised Selected Papers. ed. / Kangshun Li; Jin Li; Yong Liu; Aniello Castiglione. Springer Verlag, 2016. p. 464-473 (Communications in Computer and Information Science; Vol. 575).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - A Kuramoto Model Based Approach to Extract and Assess Influence Relations

AU - Trovati, Marcello

AU - Castiglione, Aniello

AU - Bessis, Nik

AU - Hill, Richard

PY - 2016/1/19

Y1 - 2016/1/19

N2 - 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.

AB - 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.

KW - Data analytics

KW - Information extraction

KW - Knowledge discovery

UR - http://www.scopus.com/inward/record.url?scp=84958025958&partnerID=8YFLogxK

U2 - 10.1007/978-981-10-0356-1_49

DO - 10.1007/978-981-10-0356-1_49

M3 - Conference contribution

SN - 9789811003554

T3 - Communications in Computer and Information Science

SP - 464

EP - 473

BT - Computational Intelligence and Intelligent Systems

A2 - Li, Kangshun

A2 - Li, Jin

A2 - Liu, Yong

A2 - Castiglione, Aniello

PB - Springer Verlag

ER -

Trovati M, Castiglione A, Bessis N, Hill R. A Kuramoto Model Based Approach to Extract and Assess Influence Relations. In Li K, Li J, Liu Y, Castiglione A, editors, Computational Intelligence and Intelligent Systems: 7th International Symposium, ISICA 2015, Guangzhou, China, November 21-22, 2015, Revised Selected Papers. Springer Verlag. 2016. p. 464-473. (Communications in Computer and Information Science). https://doi.org/10.1007/978-981-10-0356-1_49