An intelligent research environment on cotton diseases and pests based on a cotton phytosanitary surveillance ontology ontoSYSPARCOTCI.

Abstract

User-centred systems need to incorporate solutions to make them easier to use. Based on a domain ontology, our system has an extensive knowledge base that is populated by a semantic web platform that we have built. This knowledge base needs to be queried on demand by users due to the limitations of the search engine integrated into the semantic web platform. However, this task is not trivial for a human being due to the complexity of the schemas making up the knowledge base and the inability to perform SPARQL queries to obtain answers. In this paper, we propose an approach based on skills questions that we have defined with domain experts and that have helped validate our domain ontology. This approach allows users to ask their questions in natural language to obtain an answer. To achieve our goal, we used natural language processing tools, in particular Spacy's pre-trained French pipeline. The TF-IDF weighting method was used to calculate the similarity score between two sentences.