Measures of semantic similarity and relatedness in the biomedical domain
Journal of Biomedical Informatics
Semantic Clustering Using Multiple Ontologies
Proceedings of the 2010 conference on Artificial Intelligence Research and Development: Proceedings of the 13th International Conference of the Catalan Association for Artificial Intelligence
An ontology-based measure to compute semantic similarity in biomedicine
Journal of Biomedical Informatics
A semantic similarity method based on information content exploiting multiple ontologies
Expert Systems with Applications: An International Journal
Semantic similarity estimation from multiple ontologies
Applied Intelligence
Towards the estimation of feature-based semantic similarity using multiple ontologies
Knowledge-Based Systems
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This thesis presents novel measures to estimate the degree of semantic similarity between words using one or more knowledge sources. Several evaluations show that they improve the accuracy of related works. These measures have been applied to clustering to compute the similarity/distance between individuals described by textual attributes. Clustering results show that a proper interpretation of textual data at a semantic level improves the quality of the clusters and ease their interpretation.