PERSONAL DE APOYO
GALLO Cristian Andres
congresos y reuniones científicas
Título:
Biclustering in Data Mining using a Memetic Multi-Objective Evolutionary Algorithm
Autor/es:
GALLO, CRISTIAN ANDRÉS; MAGUITMAN, ANA GABRIELA; CARBALLIDO, JESSICA ANDREA; PONZONI, IGNACIO
Lugar:
Chilecito
Reunión:
Congreso; CACIC 2008 (XIV Congreso Argentino de la Ciencia de la Computación); 2008
Institución organizadora:
Red UNCI (Red de Universidades con Carreras de Informática), UNdeC (Universidad Nacional de Chilecito)
Resumen:
In this paper, a new memetic strategy that integrates a multi-objective evolutionary algorithm (the SPEA2) with a local search technique for data mining is presented. The algorithm explores a Term Frequency-Inverse Document Frequency (TF-IDF) data matrix in order to find biclusters that fulfill several objectives. The case of study was a dataset corresponding to the Reuters-21578 corpus. Our algorithm performed satisfactorily, finding biclusters that have large size and coherent values, yielding to undeniably promising outcomes. Nonetheless, more experiments with data from other corpus are necessary, thus leading to more concluding results.
