Abstract
The article describes the methodology to develop intelligent systems that are intended to address the reaction capacity identification problem, which can only be solved (at least partially) by professional chemists. The chosen approach can be called ontological since it starts with the ontology models. Utilizing the system approach, we start with the “Systems” meta-ontology model development. “Chemical compounds and their electron properties” ontology model is developed in the terms of “Systems” meta-ontology model. This ontology model has several modules at each system’s level. These modules contain entities associated with each system’s subsystem. These ontology models are at the heart of meta-ontology editor, “Chemical compounds and their electron properties” ontology editor, and knowledge editors. Knowledge engineers and chemists work together to fill the editors with relevant information. Since chemical compound structural formula input is the essential system interface, the JSME component has been introduced to the system. End users enter the chemical compound, they are interested in, into the intelligent system with the help of JSME. The intelligent system, in its turn, analyzes the parent compound structure, searches for the functional fragments that the parent compound possesses in its knowledge base, analyzes several characteristics found, and reasons on the reaction capacity of the parent compound. The prototype of the intelligent system is provided. It is written with the help of the Django framework.
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The reported study was funded by RFBR, project number 19-37-90137.
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Gulyaeva, K.A., Artemieva, I.L. (2022). Reaction Capacity Identification Problem: Is There Any Way to Formalize Scientific Knowledge and Automate Reasoning so that Intelligent Systems Can Solve It?. In: Nagar, A.K., Jat, D.S., Marín-Raventós, G., Mishra, D.K. (eds) Intelligent Sustainable Systems. Lecture Notes in Networks and Systems, vol 333. Springer, Singapore. https://doi.org/10.1007/978-981-16-6309-3_72
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