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Numerical Taxonomy aims to group in clusters, using so-called structure analysis of operational taxonomic units (OTUs or taxons or taxa) through numerical methods. Clusters that consitute families was the purpose of this...

Document classification has already been widely studied. In fact, some studies compared feature selection techniques or feature space transformation whereas some others compared the performance of different algorithms. R...

In the information age, knowledge leads to profits, power and success. As an ancestor of data mining, machine learning has concerned itself with discovery of new knowledge on its own. This paper presents experiment resul...

Rough Sets Theory has opened new trends for the development of the Incomplete Information Theory. Inside this one, the notion of reduct is a very significant one, but to obtain a reduct in a decision system is an expensi...

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 Docum...

Atualmente há uma enorme necesidade de adaptação das empresas ao mercado globalizado. A personalização de servidores Web contribui de maneira decisiva para manutenção de clientes neste mercado. Este artigo apresen...

Data mining is the discovery of patterns and regularities from large amounts of data using machine learning algorithms. This can be applied to object recognition using image processing techniques. In fruits and vegetabl...

Numerical Taxonomy aims to group in families, using so-called structure analysis of operational taxonomic units (OTUs or taxons or taxa). Clusters that constitute families with a new criterion, is the purpose of this se...

The genetic algorithms have seen applied in knowledge discovery and specially for discovering association rules. In this paper, we explore the use of di erent rule quality measures in the tness function in a genetic alg...

Los algoritmos de clustering de tipo c-means son sensibles a los valores de inicialización de los centroides y pueden quedar atrapados en extremos locales. Planteado en estos términos, el uso de enfoques aproximados pa...

La búsqueda por similitud consiste en recuperar todos aquellos objetos dentro de una base de datos que sean parecidos o relevantes a una determinada consulta. Este concepto tiene una amplia gama de aplicaciones en área...

El lenguaje de programación Prolog es uno de los principales lenguajes de la Inteligencia Artificial. Pertenece a la programación lógica y al desarrollo de bases de datos simbólicas. Existen varios descendientes com...

A mineração de regras de associação em um banco de dados de transações de vendas é uma tarefa extremamente cara em termos de tempo de processamento. Dependendo do ramo de atividade da empresa, algumas caracterís...

Poder atender las solicitudes de extracción de información de una manera efectiva ha sido uno de los principales objetivos de la comunidad de minería de textos biomédicos. Estas aplicaciones son herramientas valiosas...

Este trabajo tiene el objetivo de sumar una propuesta para la detección de casos atípicos. Es decir, detectar datos pertenecientes a una muestra que posean valores extremos que los diferencia del resto y permitan al i...

The field of machine learning (ML) is concerned with the question of how to construct algorithms that automatically improve with experience. In recent years many successful ML applications have been developed, such as da...

En este artículo, desarrollamos y evaluamos tres algoritmos probabilísticos sobre el comportamiento de acceso de usuarios que son apropiados para modelar la tasa de acceso a un sitio de Internet que contiene documentos...