Proceedings of the 17th Conference on Computer Science and Intelligence Systems

DOI: http://dx.doi.org/10.15439/2022F122

Citation: Proceedings of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 30, pages 841–844 (2022)

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Abstract. The Semantic Web concept is offering a future vision of the WorldWideWeb (WWW) where both humans and machines (man-made systems) are able to communicate and exchange knowledge. One of the challenges of Semantic Web is smart and trusted storage of knowledge in artificial systems so it can be unified, enhanced, reused, shared, communicated and distributed with added intelligence. Our research represents an important component of addressing the above challenge and exciting, cutting-edge exploration trend in the general area of developing tool for intelligence augmentation.

References

1. N. Pathak, The Future of AI. Apress, Berkeley, CA, 2017, pp. 247-259.
2. C. Sanin, E. Szczerbicki, “Experience-based Knowledge Representation SOEKS”. Cybernet Sys. 40(2), 99-122, 2009.
3. C. Sanín, L. Mancilla-Amaya, Z. Haoxi and E. Szczerbicki, “Decisional DNA: The Concept and its Implementation Platforms”, Cybernetic sand Systems, 43:2, 67-80, 2012, http://dx.doi.org/10.1080/01969722.2012.654069
4. E. Szczerbicki, C. Sanin, Knowledge Management and Engineering with Decisional DNA, Springer-Verlag, Berlin, 2020 http://dx.doi.org/10.1007/978-3-030-39601-5.
5. S. I. Shafiq, C. Sanin, C. Toro, and E. Szczerbicki, “Virtual engineering process (VEP): a knowledge representation approach for building bio-inspired distributed manufacturing DNA”, International Journal of Production Research, 54:23, 7129-7142, 2016, http://dx.doi.org/10.1080/00207543.2015.1125545
6. C. Sanin, L. Mancilla-Amaya, E. Szczerbicki, and P. CayfordHowell, (2009) “Application of a Multi-domain Knowledge Structure: The Decisional DNA”, in Intelligent Systems for Knowledge Management, N. T. Nguyen, E. Szczerbicki editors: Springer Berlin / Heidelberg, Vol. 252, http://dx.doi.org/10.1007/978-3-642-04170-9_3
7. B. Kucharski, E. Szczerbicki, “Experience database based on a workflow class system”, Foundations of Control and Management Science, no 12, 2009.
8. H. Zhang, C. Sanin, and E. Szczerbicki, “Decisional DNA-based embedded systems: A new perspective”, Systems Science, Vol. 36, 2010.
9. L. Mancilla-Amaya, E. Szczerbicki, and C. Sanín, “A proposal for a knowledge market based on quantity and quality of knowledge”, Cybernetics and Systems. 44(2-13), 2013, DOI 10.1080/01969722.2013.762233
10. M.M. Waris, C. Sanin, and E. Szczerbicki, (2019) “Establishing Intelligent Enterprise through Community of Practice for Product Innovation”, Journal of Intelligent and Fuzzy Systems, 2019 http://dx.doi.org/10.3233/JIFS-179329
11. B. Kucharski, E. Szczerbicki, “An approach to smart experience management”, Cybernetics and Systems. Vol. 42, 2011, DOI 10.1080/01969722.2011.541215
12. H.B. Jabrouni, G. Kamsu-Foguem, and C. Vaysse, “Continuous improvement through knowledge-guided analysis in experience feedback”, Engineering Applications of Artificial Intelligence 24(8), 2011.
13. H. Zhang, C. Sanín, and E. Szczerbicki, “Implementing fuzzy logic to generate user profile in decisional DNA television: The concept and initial case study”, Cybernetics and Systems 44(2-3), 2013, http://dx.doi.org/10.1080/01969722.2013.762280
14. C. Toro, E. Sanchez, E. Carrasco, L. Mancilla-Amaya, C. Sanín, E. Szczerbicki, M. Graña, P. Bonachela, C. Parra, and G. Bueno, “Using set of experience knowledge structure to extend a rule set of clinical decision support system for Alzheimer's disease diagnosis”, Cybernetics and Systems, 43(2), 2013, http://dx.doi.org/10.1016/j.procs.2014.08.141
15. B. A. Muhammad, S.I. Shafiq, C. Sanin, and E. Szczerbicki , “Towards Experience-Based Smart Product Design for Industry 4.0”, Cybernetics and Systems, 50:2, 165-175, 2019, http://dx.doi.org/10.1080/01969722.2019.1565123
16. M.M. Waris, C. Sanin, and E. Szczerbicki, “Toward Smart Innovation Engineering: Decisional DNA-Based Conceptual Approach”, Cybernetics and Systems, 47:1-2, 149-159, 2016, http://dx.doi.org/10.1080/01969722.2016.1128775
20. T. de Souza Alves, de Oliveira C.S., C. Sanin, and E. Szczerbicki, (2018), “Knowledge-based Vision Systems: A Review”, Proceedings of Knowledge-Based Intelligent Information and Engineering Systems 22 nd International Conference KES 2018, in Advances in Knowledge-Based and Intelligent Information and Engineering Systems: R. J. Howlett, L. C. Jain (Eds.), Belgrade, Sep 2018, Elsevier Procedia Computer Science, 2018, http://dx.doi.org/10.1016/j.procs.2018.08.077 H. Zhang, F. Li, J. Wang, and E. Szczerbicki, “A Novel IoT-Perceptive Human Activity Recognition (HAR) Approach Using Multi-Head Convolutional Attention”, IEEE Internet of Things Journal, 7, 2019, http://dx.doi.org/10.1109/jiot.2019.2949715 de Oliveira, C. S., C. Sanin, and E. Szczerbicki, (2019). “Towards Knowledge Formalization and Sharing in a Cognitive Vision Platform for Hazard Control (CVP-HC)”. Proceedings Asian Conference on Intelligent Information and Database Systems (pp. 53-61). Springer, Cham, 2019, http://dx.doi.org/10.1016/j.procs.2020.09.179 C. Zanni-Merk, E. Szczerbicki, “Building collective intelligence through experience: the KREM model”, Journal of Intelligent and Fuzzy Systems, http://dx.doi.org/10.3233/JIFS-179327, 2019.