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dc.contributor.authorGatzioura, Anna
dc.contributor.authorSànchez-Marrè, Miquel
dc.contributor.authorGibert, Karina
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa
dc.date.accessioned2020-04-28T12:04:08Z
dc.date.available2020-04-28T12:04:08Z
dc.date.issued2019-09-16
dc.identifier.citationGatzioura, A.; Sànchez-Marrè, M.; Gibert, K. A hybrid recommender system to improve circular economy in industrial symbiotic networks. "Energies", 16 Setembre 2019, vol. 12, núm. 18, p. 3546: 1-3546: 24.
dc.identifier.issn1996-1073
dc.identifier.urihttp://hdl.handle.net/2117/185448
dc.description.abstractRecently, the need of improved resource trading has arisen due to resource limitations and energy optimization problems. Various platforms supporting resource exchange and waste reuse in industrial symbiotic networks are being developed. However, the actors participating in these networks still mainly act based on predefined patterns, without taking the possible alternatives into account, usually due to the difficulty of properly evaluating them. Therefore, incorporating intelligence into the platforms that these networks use, supporting the involved actors to automatically find resources able to cover their needs, is still of high importance both for the companies and the whole ecosystem. In this work, we present a hybrid recommender system to support users in properly identifying the symbiotic relationships that might provide them an improved performance. This recommender combines a graph-based model for resource similarities, while it follows the basic case-based reasoning processes to generate resource recommendations. Several criteria, apart from resource similarity, are taken into account to generate, each time, the list of the most suitable solutions. As highlighted through a use case scenario, the proposed system could play a key role in the emerging industrial symbiotic platforms, as the majority of them still do not incorporate automatic decision support mechanisms.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa
dc.subject.lcshCircular economy
dc.subject.otherHybrid recommender systems
dc.subject.otherIndustrial symbiotic networks
dc.subject.otherCase-based reasoning
dc.subject.otherWaste optimization
dc.subject.otherEnergy consumption optimization
dc.titleA hybrid recommender system to improve circular economy in industrial symbiotic networks
dc.typeArticle
dc.subject.lemacEconomia circular
dc.contributor.groupUniversitat Politècnica de Catalunya. KEMLG - Grup d'Enginyeria del Coneixement i Aprenentatge Automàtic
dc.identifier.doi10.3390/en12183546
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::49 Calculus of variations and optimal control; optimization
dc.relation.publisherversionhttps://www.mdpi.com/1996-1073/12/18/3546
dc.rights.accessOpen Access
local.identifier.drac25854941
dc.description.versionPostprint (published version)
local.citation.authorGatzioura, A.; Sànchez-Marrè, M.; Gibert, Karina
local.citation.publicationNameEnergies
local.citation.volume12
local.citation.number18
local.citation.startingPage3546: 1
local.citation.endingPage3546: 24


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