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dc.contributor.authorAlmonte, Lissettees_ES
dc.contributor.authorPérez-Soler, Sara es_ES
dc.contributor.authorGuerra Sánchez, Esther es_ES
dc.contributor.authorCantador Gutiérrez, Iván es_ES
dc.contributor.authorLara Jaramillo, Juan de es_ES
dc.date.accessioned2022-11-16T16:12:38Zes_ES
dc.date.available2022-11-16T16:12:38Zes_ES
dc.date.issued2021-10-17es_ES
dc.identifier.citationACM Proceedings of the 14th ACM SIGPLAN International Conference on Software Language Engineering (SLE), 2021. 22-35en_US
dc.identifier.isbn978-1-4503-9111-5es_ES
dc.identifier.urihttp://hdl.handle.net/10486/705243en_US
dc.description.abstractWe are witnessing an increasing interest in building recommender systems (RSs) for all sorts of Software Engineering activities. Modelling is no exception to this trend, as modelling environments are being enriched with RSs that help building models by providing recommendations based on previous solutions to similar problems in the same domain. However, building a RS from scratch requires considerable effort and specialized knowledge. To alleviate this problem, we propose an automated approach to the generation of RSs for modelling languages. Our approach is model-based, and we provide a domain-specific language called Droid to configure every aspect of the RS (like the type and features of the recommended items, the recommendation method, and the evaluation metrics). The RS so configured can be deployed as a service, and we offer out-of-the-box integration of this service with the EMF tree editor. To assess the usefulness of our proposal, we present a case study on the integration of a generated RS with a modelling chatbot, and report on an offline experiment measuring the precision and completeness of the recommendationsen_US
dc.description.sponsorshipThis project has received funding from the EU Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813884, the Spanish Ministry of Science (RTI2018-095255-B-I00) and the R&D programme of Madrid (P2018/TCS-4314)en_US
dc.format.extent15 pag.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoengen_US
dc.publisherAssociation for Computing Machineryen_US
dc.relation.ispartofSLE 2021 - Proceedings of the 14th ACM SIGPLAN International Conference on Software Language Engineering, co-located with SPLASH 2021en_US
dc.rights© Association for Computring Machineryen_US
dc.subject.otherDomain-specific languagesen_US
dc.subject.otherModel-driven engineeringen_US
dc.subject.otherModelling languagesen_US
dc.subject.otherRecommender systemsen_US
dc.titleAutomating the synthesis of recommender systems for modelling languagesen_US
dc.typeconferenceObjecten_US
dc.subject.ecienciaInformáticaes_ES
dc.relation.publisherversionhttps://doi.org/10.1145/3486608.3486905en_US
dc.identifier.doi10.1145/3486608.3486905es_ES
dc.identifier.publicationfirstpage22es_ES
dc.identifier.publicationlastpage35es_ES
dc.identifier.publicationvolumeSLE 2021 - Proceedings of the 14th ACM SIGPLAN International Conference on Software Language Engineering, co-located with SPLASH 2021en_US
dc.relation.eventdateOctober, 21en_US
dc.relation.eventnumber14es_ES
dc.relation.eventplaceChicago (USA)en_US
dc.relation.eventtitle14th ACM SIGPLAN International Conference on Software Language Engineering, SLE; co-located with SPLASH, 2021en_US
dc.relation.projectIDGobierno de España. RTI2018-095255-B-I00es_ES
dc.type.versioninfo:eu-repo/semantics/acceptedVersionen_US
dc.rights.accessRightsopenAccessen_US


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