Ontology based semantic clustering
- Batet Sanromà, Montserrat
- Aïda Valls Mateu Director
- Karina Gibert Oliveras Director
Defence university: Universitat Rovira i Virgili
Fecha de defensa: 15 February 2011
- Salvatore Greco Chair
- Antonio Moreno Ribas Secretary
- Miquel Sànchez Marrè Committee member
- Salvador Antón Clavé Committee member
- Luis Martínez López Committee member
Type: Thesis
Abstract
Clustering algorithms have focused on the management of numerical and categorical data. However, in the last years, textual information has grown in importance. Proper processing of this kind of information within data mining methods requires an interpretation of their meaning at a semantic level. In this work, a clustering method aimed to interpret, in an integrated manner, numerical, categorical and textual data is presented. Textual data will be interpreted by means of semantic similarity ¿ [+]measures. These measures calculate the alikeness between words by exploiting one or several knowledge sources. In this work we also propose two new ways of compute semantic similarity based on 1) the exploitation of the taxonomical knowledge available on one or several ontologies and 2) the estimation of the information distribution of terms in the Web. Results show that a proper interpretation of textual data at a semantic level improves clustering results and eases the interpretability of the classifications [-