Automatic Ontology-based Annotation of Food, Nutrition and Health Arabic Web Content

Abstract

To have a successful semantic Web, it is critically required to have sufficient amount of relevant semantic and high-quality Web content. One way to produce such content is through the semantic annotation of the Web sources. Semantic annotation is the process of adding machine-readable content to the natural language textual content of the Web sources. Annotating Web content in Arabic language has received less attention compared to Latin Languages especially for content related to specific domains such as food, nutrition and health. Considering the huge amount of emerging Web content, semantic annotation of their contents by hand is neither practicable nor scalable. In this paper, we present an automatic annotation of the Arabic Web resources related to food, nutrition and health domains. The proposed method makes use of developed Arabic OWL ontologies related to those domains. It uses linguistic patterns to discover relevant relationships between the named entities in the Arabic Web resources. The extracted information is then associated to the corresponding concepts and object properties of the developed ontology to produce the RDF metadata for the corresponding Web resources. Empirical evaluations of the proposed method show promising precision and recall. As a contribution, the produced RDF triples could be utilized by semantic Web searching application to retrieve intelligent and relevant answers to end user's quires.