Extending ACO for fast path search in huge graphs and social networks

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dc.contributor.author Calle Gómez, Francisco Javier
dc.contributor.author Rivero Espinosa, Jessica
dc.contributor.author Cuadra Fernández, María Dolores
dc.contributor.author Isasi, Pedro
dc.date.accessioned 2020-09-30T09:56:54Z
dc.date.available 2020-09-30T09:56:54Z
dc.date.issued 2017-11-15
dc.identifier.bibliographicCitation Calle, J., Rivero, J., Cuadra, D., Isasi, P. (2017). Extending ACO for fast path search in huge graphs and social networks. Expert Systems with Applications, 86, pp. 292-306
dc.identifier.issn 0957-4174
dc.identifier.uri http://hdl.handle.net/10016/30904
dc.description.abstract This paper presents the bio-inspired algorithm SoSACO-v2 that is explained as an extension of the Ant Colony Optimization in which the ants are empowered with the sense of smell, directing them straightly to privileged nodes when they are near enough of them. This algorithm is an evolution of a former version which main feature is efficiency through path search task in huge graphs of high connectivity. New requirements regarding this task in most applications include processing vast graphs, immediate comeback, and dealing with dynamicity. The here proposed algorithm gives response to new needs the former approaches cannot fulfill: fast finding of paths between two nodes through vast dynamic graphs. SoSACO-v2 does not provide the optimum path, but it is the quicker algorithm in providing a response. It stands for domains where optimality is not required, and often the path search takes more time than covering the path. The approach is evaluated, both in a generic huge graph and in a small-world type graph from a real social network, showing satisfactory results.
dc.description.sponsorship This study was partially funded by the Spanish Ministry of Industry, Tourism and Commerce through the CADOOH research project ( TSI-020302201121 ), and the Spanish Ministry of Sci- ence and Innovation under the MOVES research project ( TIN- 201128336 ). Our sincere thanks to everyone involved in those projects, and to all who have supported us during this work.
dc.language.iso eng
dc.publisher Elsevier
dc.rights © 2017 Elsevier Ltd. All rights reserved.
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Huge Graphs
dc.subject.other Aco
dc.subject.other Bio inspired algorithms
dc.subject.other Path search
dc.subject.other Social networks
dc.title Extending ACO for fast path search in huge graphs and social networks
dc.type article
dc.subject.eciencia Informática
dc.identifier.doi https://doi.org/10.1016/j.eswa.2017.05.066
dc.rights.accessRights closedAccess
dc.relation.projectID Gobierno de España. TIN2011-28336
dc.relation.projectID Gobierno de España. TSI-020302201121
dc.type.version publishedVersion
dc.identifier.publicationfirstpage 292
dc.identifier.publicationlastpage 306
dc.identifier.publicationtitle EXPERT SYSTEMS WITH APPLICATIONS
dc.identifier.publicationvolume 86
dc.identifier.uxxi AR/0000020355
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