Chhetri, Tek Raj (2021) Improving decision making using semantic web technologies. In, Verborgh, Ruben, Dimou, Anastasia, Hogan, Aidan, d'Amato, Claudia, Tiddi, Ilaria, Bröring, Arne, Mayer, Simon, Ongenae, Femke, Tommasini, Riccardo and Alam, Mehwish (eds.) The Semantic Web: ESWC 2021 Satellite Events. (Lecture Notes in Computer Science) ESWC 2021 Satellite Events (06/06/21 - 10/06/21) Springer Cham, 165–175. (doi:10.1007/978-3-030-80418-3_29).
Abstract
With the rapid advance of technology, we are moving towards replacing humans in decision making–the employment of robotics and computerised systems for production and delivery and autonomous cars in the travel sector. The focus is placed on the use of techniques, such as machine learning and deep learning. However, despite advances in machine learning and deep learning, they are incapable of modelling the relationships that are present in the real world, which are necessary for making a decision. For example, automating sociotechnical systems requires an understanding of both human and technological aspects and how they influence one another. Using machine learning, we can not model the relationships of a sociotechnical systems. Semantic Web technologies, which is based on the concept of linked-data technology, can represent relationships in a more realistic way like in the real world, and be useful to make better decisions. The study looks at the use of Semantic Web technologies, namely ontologies and knowledge graphs to improve decision making process.
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