Psychological named entity recognition from psychological Arabic texts
by Kheira Lakel; Fatima Bendella
International Journal of Metadata, Semantics and Ontologies (IJMSO), Vol. 12, No. 2/3, 2017

Abstract: The most important problems facing the Arabisation of modern science is the terminological inconsistency in translation; this problem becomes more complex in the medical field specifically in psychological sciences where the translation of English-Arabic medical terms poses real challenges for researchers eager to analyse and organise this information. Arabic NER (Named Entity Recognition) systems play a significant role in many areas of Natural Language Processing (NLP). In this paper, the problem of PsyNER (Psychological Named Entity Recognition) is tackled through integrating the rule-based and machine learning based approach to form a hybrid approach in attempt to enhance the overall performance of PsyNER. This system is capable to recognise eight types of named entities including mental disorders designated by the DSM-IV (Diagnostic and Statistical Manual of the American Psychiatric Association).

Online publication date: Tue, 27-Mar-2018

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