Weighted Graphs to Redefine the Centrality Measures

López González, M. Dolores ORCID: https://orcid.org/0000-0002-9974-7918, Rodrigo Hitos, Javier, Puente, Cristina and Olivas Varela, José Ángel (2019). Weighted Graphs to Redefine the Centrality Measures. In: "Mathematical Modelling in Engineering & Human Behavior 2018", 16-18 julio 2018, Valencia, España.

Description

Title: Weighted Graphs to Redefine the Centrality Measures
Author/s:
Item Type: Presentation at Congress or Conference (Other)
Event Title: Mathematical Modelling in Engineering & Human Behavior 2018
Event Dates: 16-18 julio 2018
Event Location: Valencia, España
Title of Book: Mathematical Modelling for Engineering, & Human Behaviour 2017
Date: 15 April 2019
Subjects:
Freetext Keywords: Weighted Causal Graphs, Causality, Causal Model, Causal Representation, Centrality Measures
Faculty: E.T.S.I. Caminos, Canales y Puertos (UPM)
Department: Matemática e Informática Aplicadas a la Ingenierías Civil y Naval
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Causal graphs are a very useful tool to connect information and study to what extent an effect is provoked by a cause. In this paper we explore the role of weighted graphs to evaluate the degree in which a sentence is direct or indirect cause of an effect, to obtain the path with a highest causality degree between two concepts, and on the other hand, given a context, the two concepts with a strongest causal relationship. We also define some centrality measures, introducing causality degrees and weighted graphs to evaluate the centrality measure of the sentences getting the more relevant sentences from a causal point of view.

Funding Projects

Type
Code
Acronym
Leader
Title
Government of Spain
TIN2016-76843-C4-2-R
MERINET
Unspecified
Métodos rigurosos para el internet del futuro
Government of Spain
TIN2014-56633-C3-1-R
Unspecified
Unspecified
Soft Computing para soporte a la inteligencia de negocio social Workflows

More information

Item ID: 57640
DC Identifier: https://oa.upm.es/57640/
OAI Identifier: oai:oa.upm.es:57640
Deposited by: Memoria Investigacion
Deposited on: 06 Mar 2020 13:22
Last Modified: 06 Mar 2020 13:22
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