A Kuramoto Model Based Approach to Extract and Assess Influence Relations

Marcello Trovati; Aniello Castiglione; Nik Bessis; Richard Hill

doi:10.1007/978-981-10-0356-1_49

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 proceeding › Conference contribution › peer-review

6 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 language	English
Title of host publication	Computational Intelligence and Intelligent Systems
Subtitle of host publication	7th International Symposium, ISICA 2015, Guangzhou, China, November 21-22, 2015, Revised Selected Papers
Editors	Kangshun Li, Jin Li, Yong Liu, Aniello Castiglione
Publisher	Springer Verlag
Pages	464-473
Number of pages	10
ISBN (Electronic)	9789811003561
ISBN (Print)	9789811003554
DOIs	https://doi.org/10.1007/978-981-10-0356-1_49
Publication status	Published - 19 Jan 2016
Externally published	Yes
Event	7th International Symposium on Computational Intelligence and Intelligent Systems - Guangzhou, China Duration: 21 Nov 2015 → 22 Nov 2015 Conference number: 7

Publication series

Name	Communications in Computer and Information Science
Publisher	Springer
Volume	575
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	7th International Symposium on Computational Intelligence and Intelligent Systems
Abbreviated title	ISICA 2015
Country/Territory	China
City	Guangzhou
Period	21/11/15 → 22/11/15

Access to Document

10.1007/978-981-10-0356-1_49Licence: Unspecified

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 et al. / 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).

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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 = jan,

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",

address = "Germany",

note = "7th International Symposium on Computational Intelligence and Intelligent Systems , ISICA 2015 ; Conference date: 21-11-2015 Through 22-11-2015",

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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 et al.

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 proceeding › Conference contribution › peer-review

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

N1 - Conference code: 7

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

AN - SCOPUS:84958025958

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

T2 - 7th International Symposium on Computational Intelligence and Intelligent Systems

Y2 - 21 November 2015 through 22 November 2015

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). doi: 10.1007/978-981-10-0356-1_49

A Kuramoto Model Based Approach to Extract and Assess Influence Relations

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