The Method of Semantic Modeling
DOI:
https://doi.org/10.71310/pcam.5_69.2025.09Keywords:
informational modeling, semantic structure, attribute representation, cognitive systems, data interpretationAbstract
This paper presents a method of semantic modeling based on representing complex objects and phenomena as informational aggregates composed of core, designating, characterizing, and associative entities. Each entity is described by a set of attributes, and their interactions are governed by semantic operation algorithms that generate new informational structures. This approach enables a transition from formal syntactic data representation to meaningful semantic interpretation. The proposed method can be applied to the development of expert and cognitive systems that perform machine understanding and semantic information processing within the field of artificial intelligence.
References
Rustamov N., Amirtayev K. A heuristic model for evaluating the mental qualities of a leader // Problems of Computational and Applied Mathematics. – 2025. – No. 2(64). – P. 46-53. – doi: http://dx.doi.org/10.71310/pcam.2_64.2025.04.
Rustamov N.T., Amirtayev K.B. Computer Simulation of Human Psychological Symbiosis // Bulletin of the International Kazakh-Turkish University named after Khoja Akhmet Yassawi (Mathematics, Physics, Informatics Series). – 2025. – .1(32). – doi: http://dx.doi.org/10.47526/3007-8598-2025.1-15.
Rustamov N.T., Rustamov Y.K. Infological Model of TERRORISM against the Background of Social Stratification (Modeling Terrorism). – Germany: LAP LAMBERT Academic Publishing, 2014. – 122 p.
Rustamov N.T., Israilov R.I., Rustamov B.K. On the Issue of Designing a Knowledge Base (Using Stroke as an Example). – Tashkent: Innovatsion rivozhlanish nashriyot-matbaa uyi, 2020. – 112 p.
Alonso H.M., Plank B. When is multitask learning effective? Semantic sequence prediction under varying data conditions // EACL. – 2016. – Vol. 1. – P. 44-53.
Liu P., Qiu X., Huang X. Recurrent Neural Network for Text Classification with Multi-Task Learning // Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16). – 2016. – P. 2873-2879.
McCoss A. Yin Yang Cosmology // Journal of Modern Physics. – 2023. – Vol. 14, No. 7. – doi: http://dx.doi.org/10.4236/jmp.2023.147061.
Wu K., Wu L., Huang Z., Jiang Y., Ma Y. Journal of Materials Science and Chemical Engineering. – 2015. – Vol. 3, No. 7. – doi: http://dx.doi.org/10.4236/msce.2015.37011.
Lan Z., Chen M., Goodman S., Gimpel K., Sharma P., Soricut R. ALBERT: A Lite BERT for Self-Supervised Learning of Language Representations. – 2020. – https://arxiv.org/abs/1909.11942.
Rustamov N.T., Temirbekov A.N., Rustamov B.K., Anarbaev Zh.O. Semantic Model of Energy-Informational Medicine // Bulletin of IKTU named after H.A. Yassawi. – 2008. – No. 3. – P. 121-131.
Israilov R.I., Rustamov N.T., Rustamov B.K. Mathematical Method for Clinical Prediction of Morphological and Morphometric Changes in Cerebral Vessels During Stroke. Mathematical Morphology // Electronic Journal of Mathematical and Biomedical Research. – 2009. – Vol. 8, No. 1. – P. 7-15.
Rustamov N.T., Temirbekov A.N., Kantureeva M.A., Asilbayeva A.P. Evaluation of Knowledge Semantics // Bulletin of KarGU. – 2009. – No. 2(54). – P. 52-56.
Muhamediyeva D.T., Rustamov E.N. Semantic Representation of Production Knowledge // International Conference on Information Science and Communications Technologies (ICISCT). – 2022. – doi: http://dx.doi.org/10.1109/ICISCT55600.2022.10146951.
Heppner W.L., Kernis M.H., Nezlek J.B., Foster J., Lakey C.E., Goldman B.M. Within-Person Relationships Among Daily Self-Esteem, Need Satisfaction, and Authenticity // Psychological Science. – 2008. – Vol. 19, No. 11. – P. 1140-1145. – doi: http://dx.doi.org/10.1111/j.1467-9280.2008.02215.x.
Rochat P. Five levels of self-awareness as they unfold early in life // Consciousness and Cognition. – 2003. – Vol. 12. – P. 717-731. – doi: http://dx.doi.org/10.1016/S1053-8100(03)00081-3.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 N. Rustamov
This work is licensed under a Creative Commons Attribution 4.0 International License.
