Titlebook: Mathematical Modelling Programs in Latin America; A Collaborative Cont Milton Rosa,Francisco Cordero,Pablo Carranza Book 2022 The Editor(s)

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Alcione Marques Fernandes,Cristiane Castro Pimentel,Nayane Rodrigues de Deuser item-indexable databases with heightened efficiency. Second, we propose a pattern-merging procedure, MergeIndexBic, to efficiently discover lengthy noise-tolerant sequential patterns. The superior performance of IndexSpan and MergeIndexBic against competitive alternatives is demonstrated on both

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Juan Ramón Cadena,Ronald Patricio Chasiloa Llumiquingainteractions between resources operating at the data window level. Finally, it integrates specific algorithms, in order to discover (overlapping) communities of resources and track the evolution of these communities over consecutive windows. This paper applies the defined framework to two real event

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le to swiftly adapt to changes. Rather, the data mining techniques should also be fast, scalable, and efficient in terms of resource allocation. It then becomes important to consider Return on Investment (ROI) issues such as storage space needs and memory utilization. This paper introduces the Adapt

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Pablo Carranza,Fabio Miguelinteractions between resources operating at the data window level. Finally, it integrates specific algorithms, in order to discover (overlapping) communities of resources and track the evolution of these communities over consecutive windows. This paper applies the defined framework to two real event

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Pablo Carranza,Jaime Morenointeractions between resources operating at the data window level. Finally, it integrates specific algorithms, in order to discover (overlapping) communities of resources and track the evolution of these communities over consecutive windows. This paper applies the defined framework to two real event

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OATH

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We propose a system that measures the similarity of a new patient to existing clusters, and makes a personalized decision on the patient’s most likely negative side effects. We further evaluate our system using SID, which is part of the Healthcare Cost and Utilization Project (HCUP). Our experiment

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Francisco Cordero,E. Johanna Mendoza-Higuera,Irene Pérez-Oxté,Jaime Huincahue,Jaime Mena-Lorcai-target regression (MTR), a?type of structured output prediction, where the output space consists of multiple numerical values. Our main objective is to investigate whether we can improve over supervised methods for MTR by using unlabeled data. We use ensembles of predictive clustering trees in a s

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