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Cluster: um software para auxílio em estudos de dados biológicos
(Universidade Federal de Minas GeraisUFMG, 2015-11-16)
The ever increasing availability of biological data gives rise to two problems: (i) data storage and management and (ii) the extraction of useful information from these data. The latter problem is one of the main challenges ...
Interpretable interval type-2 fuzzy predicates for data clustering: A new automatic generation method based on self-organizing maps
(Elsevier Science, 2017-10)
In previous works, we proposed two methods for data clustering based on automatically discovered fuzzy predicates which were referred to as SOM-based Fuzzy Predicate Clustering (SFPC) [Meschino et al., Neurocomputing, 147, ...
Colombian university supply analysis
(2021)
Considering the market conditions of high competence and decreased demand, universities must work under a market vision and build solid strategies based on data to make better decisions and improve their competitive position. ...
A Method to Improve the Analysis of Cluster Ensembles
(Sociedad Iberoamericana de Inteligencia Artificial, 2014-03)
Clustering is fundamental to understand the structure of data. In the past decade the cluster ensembleproblem has been introduced, which combines a set of partitions (an ensemble) of the data to obtain a singleconsensus ...
QuickDBC: uma separação rápida de clusters baseada em densidade para espaços métricos
(Universidade Tecnológica Federal do ParanáPato BrancoBrasilDepartamento Acadêmico de InformáticaEngenharia de ComputaçãoUTFPR, 2018-12-06)
The class identification task for spatial databases can be achieved by clustering algorithms. However, it requires a domain knowledge to determine some input parameters to discover clusters and the improvement of its ...
Heuristics for minimizing the maximum within-clusters distance
(Sociedade Brasileira de Pesquisa Operacional, 2012)
The clustering problem consists in finding patterns in a data set in order to divide it into clusters with high within-cluster similarity. This paper presents the study of a problem, here called MMD problem, which aims at ...
ClusMAM: fast and effective unsupervised clustering of large complex datasets using metric access methods
(Association for Computing Machinery - ACMUniversity of PisaScuola Superiore Sant’AnnaPisa, 2016-04)
An efficient and effective clustering process is a core task of data mining analysis, and has become more important in the nowadays scenario of big data, where scalability is an issue. In this paper we present the ClusMAM ...
Heuristics for minimizing the maximum within-clusters distance
(Sociedade Brasileira de Pesquisa Operacional, 2012-12-01)
The clustering problem consists in finding patterns in a data set in order to divide it into clusters with high within-cluster similarity. This paper presents the study of a problem, here called MMD problem, which aims at ...