Enhancement of Semantic Analysis Based on the Ontology Reengineering: A Case Study on Moroccan Tourism Domain

Abstract

This article outlines a novel semi-automatic approach aimed at enhancing a foundational ontology associated with Moroccan tourism. The initial phase of this methodology involved extracting new conceptual entities and semantic relationships from heterogeneous and multi-format textual resources, using a meticulously curated suite of Natural Language Processing (NLP) tools. The subsequent phase focused on aligning this updated Ontological version (OTMv1: Ontology of Tourism in Morocco version 1.0) with other external business ontologies. This was achieved through the design and development of specific terminological and structural matches to facilitate the mapping of knowledge shared by these ontological resources. The implementation of this approach resulted in the reengineering of an enhanced and semantically richer Ontology version (OTMv2). To streamline the validation tasks associated with the ontological model, particularly involving domain experts, we introduced a dedicated web platform (WebApp OTMv2) for experimentation and testing. Research conducted on this platform confirms the effectiveness of the proposed approach in enhancing the semantic quality of the outcomes within the context of Moroccan tourism.