Framework of Semantic Annotation of Arabic Document using Deep Learning

Semantic Web vision is to have machines interpret and understand the content of Web documents. There is a need to convert the existing Web of documents into an understandable format, which could be done by automatic semantic annotation. Annotation could be performed using a set of tools provided with general and domain-specific ontologies. The aim of this paper is to present a generic semantic annotation framework of Arabic text using deep learning models. The framework produces annotations using different output formats for a given set of Arabic documents and ontologies. With a prototype of the framework, the initial evaluation shows a promising performance using different public Arabic word embedding models with different vectorization and matching techniques.