A contribution of Natural Language Processing to the study of semantic memory loss in patients with Alzheimer’s disease

• Autores: María Beatriz Pérez Cabello de Alba
• Localización: LFE: Revista de lenguas para fines específicos, ISSN 1133-1127, Vol. 23, Nº 2, 2017, págs. 133-156
• Idioma: inglés
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• Dialnet Métricas: 3 Citas
• Resumen

  • This paper addresses semantic memory loss from the perspective of Natural Language Processing. Dementia disorders and, in particular, Alzheimer’s disease (AD) present a loss of cognitive functions, being one of them semantic memory impairment. We set from a study conducted by Grasso, Díaz & Peraita (2011) where they analysed the production of features of four semantic categories (2 Living Beings and 2 Non Living Beings) of healthy subjects and patients with different levels of Alzheimer’s disease, taken from the Linguistic corpus of semantic categories definitions elaborated by Peraita & Grasso (2010). The aim of this work is to enhance the protocol of semantic features employed in that study by using Natural Language Processing systems such as FunGramKB (Periñán-Pascual & Arcas Túnez 2004, 2005, 2006, 2007, 2010). This lexical-conceptual knowledge base incorporates a series of feature descriptors for the definition of semantic knowledge which, together with the inheritance and inference relations established among concepts in the ontology, will enrich the collection of semantic features used in the test of semantic attributes production for the detection of semantic memory impairment (Grasso, Díaz & Peraita, 2011).