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  •   François Achille Djontu Tajouo

  •   Thierry Noulamo

  •   Jean-Pierre Lienou

Abstract

Information Retrieval (IR) from data sources such as the web, databases, sensors, etc., and structuring it through ontologies is an ambitious research field that leads to the reduction of information search time, improvement of the quality of found information and the efficient decision making. In this work, we have proposed a system for extracting information from several data sources to enrich an ontology in the field of plant pathology. The objective of this work is to develop a knowledge base in the field of plant pathology, by structuring the data present in various data sources accessible mainly through the web. To do this, we first propose a modular development approach of a domain ontology. The construction of the ontology at first uses the text-based construction technique and then, we use the generic architecture of a web data extraction system technique from literature to propose a data extraction system for the enrichment of the different ontology modules of the domain. For each subsystem of our extraction system, we have developed the algorithms to be implemented.

Keywords: Information Retrieval, Knowledge Base, Merge ontologies, Modularization, Ontology Module, Ontology

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How to Cite
[1]
Djontu Tajouo, F.A., Noulamo, T. and Lienou, J.-P. 2021. Procedure for the Contextual, Textual and Ontological Construction of Specialized Knowledge Bases. European Journal of Electrical Engineering and Computer Science. 5, 1 (Feb. 2021), 62-67. DOI:https://doi.org/10.24018/ejece.2021.5.1.282.