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Title: A systematic mapping study about applications of knowledge graphs in agribusiness

Authors: Mario José Diván; Valerio Frittelli

Addresses: Economy School, National University of La Pampa, Santa Rosa, CP6300, Argentina ' National Technological University, Córdoba, CP5000, Argentina

Abstract: Knowledge management refers to data jointly with their meaning and relationships to foster a consistent, accessible, and integrated view of knowledge. Complemented by the recommendation strategies, it is useful for supporting different decision-making processes in intelligent systems. The knowledge graphs (KGs) allows describing entities, objects, events, or concepts, placing data in every context, fostering an articulation between data and its associated meaning. This article aims to address a broad analysis of the modelling and application of the KG in the agribusiness sector, following the systematic mapping study methodology. The Scopus, IEEE, ScienceDirect, and ACM databases are considered for performing the different queries according to the research questions aligned with the objective. The main scope of this study is constituted of articles written in the English language, published within the last ten years. Initially, a total of 156 documents are obtained. Finally, 12 are retained and considered according to the defined filters and after a careful and full reading. The KG applied in the agribusiness sector keeps being a challenge, existing different opportunities to be addressed.

Keywords: systematic mapping study; SMS; agribusiness applications; knowledge graphs; frameworks; platforms.

DOI: 10.1504/IJRIS.2022.123388

International Journal of Reasoning-based Intelligent Systems, 2022 Vol.14 No.1, pp.27 - 38

Received: 23 Aug 2021
Accepted: 28 Sep 2021

Published online: 13 Jun 2022 *

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