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dc.contributor.authorKuster Filipe Bowles, Juliana
dc.contributor.authorBroccia, Giovanna
dc.contributor.authorNanni, Mirco
dc.identifier.citationKuster Filipe Bowles , J , Broccia , G & Nanni , M 2020 , DataMod2020: 9th International Symposium From Data to Models and Back . in Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM '20) . ACM , New York , pp. 3531–3532 , 29th ACM International Conference on Information and Knowledge Management (CIKM2020) , Ireland , 19/10/20 .
dc.identifier.otherPURE: 270110320
dc.identifier.otherPURE UUID: 20b35f7b-5b5d-4539-b8c4-53ea73e0a469
dc.identifier.otherORCID: /0000-0002-5918-9114/work/82788893
dc.identifier.otherScopus: 85095863559
dc.description.abstractDataMod 2020 aims to bring together practitioners and researchers from academia, industry and research institutions interested in the combined application of computational modelling methods with data-driven techniques from the areas of knowledge management, data mining and machine learning. Modelling methodologies of interest include automata, agents, Petri nets, process algebras and rewriting systems. Application domains include social systems, ecology, biology, medicine, smart cities, governance, security, education, software engineering, and any other field that deals with complex systems and large amounts of data. Papers can present research results in any of the themes of interest for the symposium as well as application experiences, tools and promising preliminary ideas. Papers dealing with synergistic approaches that integrate modelling and knowledge management/discovery or that exploit knowledge management/discovery to develop/syntesise system models are especially welcome.
dc.relation.ispartofProceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM '20)en
dc.rightsCopyright © 2020 Owner/Author. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectZA4050 Electronic information resourcesen
dc.titleDataMod2020: 9th International Symposium From Data to Models and Backen
dc.typeConference itemen
dc.contributor.institutionUniversity of St Andrews.School of Computer Scienceen

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