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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.
Title: | Weighted Graphs to Redefine the Centrality Measures |
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Author/s: |
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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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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.
Item ID: | 57640 |
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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 |