Automatic Building of an Ontology from a Corpus of Text Documents Using Data Mining Tools

Abstract

En este artículo mostramos un procedimiento para construir automáticamente una ontología a partir de un corpus de documentos de texto sin ayuda externa tal como diccionarios o tesauros. El método propuesto encuentra conceptos relevantes en forma de frases temáticas en el corpus de documentos y relaciones no jerárquicas entre ellos de manera no supervisada.

Learning Object Retrieval and Aggregation Based on Learning Styles

“…The Merge Algorithm (MA) uses a hierarchy of concepts that represents a given LO to identify similar items between two different LOs; then, the most suitable item will be selected and added to the merged LO. A preprocessing task is conducted before using the approach described in Toledo-Alvarado, Guzmán-Arenas, and Martínez-Luna (2012) to obtain the concepts for each LO. To extract the concepts, each LO is treated as a document, and the top five LOs ranked by Equation (1) are considered the minimum support (see Toledo-Alvarado et al., 2012, for further details).…”

“…A preprocessing task is conducted before using the approach described in Toledo-Alvarado, Guzmán-Arenas, and Martínez-Luna (2012) to obtain the concepts for each LO. To extract the concepts, each LO is treated as a document, and the top five LOs ranked by Equation (1) are considered the minimum support (see Toledo-Alvarado et al., 2012, for further details). The result of this step is a hierarchy of concepts, which are mapped onto each LO item; thus, the relationships among the items are identical among the concepts in the hierarchy (see Figure 2).…”