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An evolutionary technique to approximate multiple optimal alignments
dc.contributor.author | Taymouri, Farbod |
dc.contributor.author | Carmona Vargas, Josep |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Ciències de la Computació |
dc.date.accessioned | 2019-01-17T14:55:18Z |
dc.date.available | 2019-01-17T14:55:18Z |
dc.date.issued | 2018 |
dc.identifier.citation | Taymouri, F., Carmona, J. An evolutionary technique to approximate multiple optimal alignments. A: International Conference on Business Process Management. "Business Process Management,16th International Conference, BPM 2018, Sydney, NSW, Australia, September 9-14, 2018: proceedings". Berlín: Springer, 2018, p. 215-232. |
dc.identifier.isbn | 978-3-319-98648-7 |
dc.identifier.uri | http://hdl.handle.net/2117/127144 |
dc.description.abstract | The alignment of observed and modeled behavior is an essential aid for organizations, since it opens the door for root-cause analysis and enhancement of processes. The state-of-the-art technique for computing alignments has exponential time and space complexity, hindering its applicability for medium and large instances. Moreover, the fact that there may be multiple optimal alignments is perceived as a negative situation, while in reality it may provide a more comprehensive picture of the model’s explanation of observed behavior, from which other techniques may benefit. This paper presents a novel evolutionary technique for approximating multiple optimal alignments. Remarkably, the memory footprint of the proposed technique is bounded, representing an unprecedented guarantee with respect to the state-of-the-art methods for the same task. The technique is implemented into a tool, and experiments on several benchmarks are provided. |
dc.format.extent | 18 p. |
dc.language.iso | eng |
dc.publisher | Springer |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica |
dc.subject.lcsh | Evolutionary computation |
dc.subject.lcsh | Computational complexity |
dc.subject.lcsh | Approximation theory |
dc.title | An evolutionary technique to approximate multiple optimal alignments |
dc.type | Conference report |
dc.subject.lemac | Computació evolutiva |
dc.subject.lemac | Complexitat computacional |
dc.subject.lemac | Aproximació, Teoria de l' |
dc.contributor.group | Universitat Politècnica de Catalunya. ALBCOM - Algorismia, Bioinformàtica, Complexitat i Mètodes Formals |
dc.identifier.doi | 10.1007/978-3-319-98648-7_13 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | https://link.springer.com/chapter/10.1007/978-3-319-98648-7_13 |
dc.rights.access | Open Access |
local.identifier.drac | 23568103 |
dc.description.version | Postprint (author's final draft) |
dc.relation.projectid | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-86727-C2-1-R/ES/MODELOS Y METODOS BASADOS EN GRAFOS PARA LA COMPUTACION EN GRAN ESCALA/ |
local.citation.author | Taymouri, F.; Carmona, J. |
local.citation.contributor | International Conference on Business Process Management |
local.citation.pubplace | Berlín |
local.citation.publicationName | Business Process Management,16th International Conference, BPM 2018, Sydney, NSW, Australia, September 9-14, 2018: proceedings |
local.citation.startingPage | 215 |
local.citation.endingPage | 232 |