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dc.creatorRottoli, Giovanni Daián
dc.creatorMerlino, Hernán Daniel
dc.creatorGarcía Martínez, Ramón
dc.identifier.citationAdvances in Artificial Intelligence: From Theory to Practice 10350: 221-226 (2017)es_ES
dc.description.abstractThe co-location discovery process serves to find subsets of spatial features frequently located together. Many algorithms and methods have been designed in recent years; however, finding this kind of patterns around specific spatial features is a task in which the existing solutions provide incorrect results. Throughout this paper we propose a knowledge discovery process to find co-location patterns focused on reference features using decision tree learning algorithms on transactional data generated using maximal cliques. A validation test of this process is provided.es_ES
dc.subjectCo-location patternses_ES
dc.subjectSpatial data mininges_ES
dc.subjectDecision trees algorithmses_ES
dc.subjectMaximal cliqueses_ES
dc.subjectKnowledge discovery processes_ES
dc.titleCo-location rules discovery process focused on reference spatial features using decision tree learninges_ES
dc.rights.holderRottoli, Giovanni Daián ; Merlino, Hernán Daniel ; García Martínez, Ramónes_ES
dc.description.affiliationFil: Merlino, Hernán Daniel. Universidad Nacional de Lanús; Argentina.es_ES
dc.description.affiliationFil: Rottoli, Giovanni Daián. Universidad Tecnológica Nacional.Facultad Regional Concepción del Uruguay. Departamento Ingeniería en Sistemas de Información. Grupo de Investigación en Bases de Datos; Argentina.
dc.description.affiliationFil: Rottoli, Giovanni Daián. Universidad Nacional de La Plata; Argentina.
dc.description.affiliationFil: Rottoli, Giovanni Daián. Universidad Nacional de Lanús; Argentina.
dc.description.affiliationFil: García Martínez, Ramón. Universidad Nacional de Lanús. Departamento Desarrollo Productivo y Tecnológico. Grupo de Investigación en Sistemas de Información; Argentina.
dc.description.affiliationFil: García Martínez, Ramón. Comisión de Investigaciones Científicas; Argentina.
dc.description.peerreviewedPeer Reviewedes_ES
dc.rights.useNo comercial con fines académicoses_ES
dc.rights.useAttribution-NonCommercial-NoDerivatives 4.0 Internacional*

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