Enteprise ontology based on intelligent agents. case study: knowledge based production export actors.
mohammad rahim banakar
1
(
)
ُShaban Elahi
2
(
Vali-e-Asr University Of Rafsanjan, Rafsanjan, Iran.
)
shaghayegh sahraee
3
(
Management department, faculty of management and economics, tarbiat modares university, Tehran, iran.
)
Keywords: Omtology, Intelligent agent, Knowledge management, Interoperability.,
Abstract :
To develop ontology and investigate the role of intelligent factors in enriching ontology. On the other hand, the study of trade documents in the Trade Development Organization and Iran's Export and Import Statistics in the past few years creates the need in practice to address Iran's trade weaknesses by an ontology of knowledge-based export actors. Methodology: Grounded theory (Systematic Litreture Review) Conclusion: Ontology is the formal representation of the entities of a particular domain, which makes it possible to represent tacit and explicit knowledge of a particular field as a knowledge base through field research. Intelligent agent capabilities can be used to create an automation process in the development and enrichment of ontology. A systematic review is needed to evaluate, summarize, and compile studies on ontology and intelligent agents and establish an interaction between the two. A search of the database from January 2017 to the end of 2021 identified 38 relevant articles eligible for a qualitative evaluation of 15 articles. Intelligent agents identified the following nine concepts of ontology enrichment.
[1] S. S. Rao and A. Nayak, “Enterprise ontology model for tacit knowledge externalization in socio-technical enterprise,” Interdiscip. J. Information, Knowledge, Manag., vol. 12, pp. 99–124, 2017.
[2] M. Brahimi, “An agents’ model using ontologies and web services for creating and managing virtual enterprises,” Int. J. Comput. Digit. Syst., vol. 8, no. 1, pp. 1–9, 2019, doi: 10.12785/ijcds/080101.
[3] T. R. Gruber, “Toward Principles for the Design of Ontologies,” International Journal of Human-Computer Studies, vol. 43, no. 5–6. pp. 907–928, 1995.
[4] D. Monticolo, I. Lahoud, and P. C. Barrios, “OCEAN: A multi agent system dedicated to knowledge management,” J. Ind. Inf. Integr., vol. 17, p. 100124, 2020, doi: 10.1016/j.jii.2019.100124.
[5] S. Zidat and F. Marir, “An Approach to the Acquisition of Tacit Knowledge Based on an Ontological Model Department of Computer Science , Chahid Mostefa Ben Boulaid , University of College of Technological Innovation , Zayed University , Dubai , United Arab Corresponding Author :,” J. King Saud Univ. - Comput. Inf. Sci., 2018, doi: 10.1016/j.jksuci.2018.09.012.
[6] A. Di Iorio and D. Rossi, “Capturing and managing knowledge using social software and semantic web technologies,” Inf. Sci. (Ny)., vol. 432, pp. 1–21, 2018, doi: 10.1016/j.ins.2017.12.009.
[7] Jan Andreasik, Knowledge management model based on the enterprise ontology for the KB DSS system of enterprise situation assessment in the SME sector, vol. 787. Springer International Publishing, 2019. doi: 10.1007/978-3-319-94229-2_15.
[8] B. Okreša Ɖurić, J. Rincon, C. Carrascosa, M. Schatten, and V. Julian, “MAMbO5: a new ontology approach for modelling and managing intelligent virtual environments based on multi-agent systems,” J. Ambient Intell. Humaniz. Comput., no. 0123456789, 2018, doi: 10.1007/s12652-018-1089-4.
[9] D. Chumachenko and I. Meniailov, “Development of an intelligent agent-based model of the epidemic process of syphilis,” csit, vol. 2, pp. 17–20, 2019.
[10] Y. Wang, L. Wang, and C. Wang, “Research on Ontology-Based Tacit Knowledge Mining for Aerospace Enterprise,” J. Phys. Conf. Ser., vol. 1087, no. 3, 2018, doi: 10.1088/1742-6596/1087/3/032018.
[11] A. Smirnov, A., Levashova, T. and Kashevnik, Enterprise Ontology for Service Interoperability in Socio-Cyber-Physical Systems. In Enterprise Interoperability VIII, vol. 9. Springer International Publishing, 2019. doi: 10.1007/978-3-030-13693-2.
[12] Y. Chemlal, “Onto-agent-SSSN: An ontology model to facilitate reactive reasoning in multi-agent systems within a business intelligence network,” Int. J. Reason. Intell. Syst., vol. 11, no. 3, pp. 282–291, 2019, doi: 10.1504/IJRIS.2019.102635.
[13] J. U. the blockchain using enterprise ontology. de Kruijff, J. and Weigand, H., 2017, “Understanding the Blockchain Using Enterprise Ontology,” Int. Conf. Adv. Inf. Syst. Eng. Springer, Cham., pp. 29–43, 2017, doi: 10.1007/978-3-319-59536-8.
[14] J. Liu et al., “Grid workflow validation using ontology-based tacit knowledge: A case study for quantitative remote sensing applications,” Comput. Geosci., vol. 98, pp. 46–54, 2017, doi: 10.1016/j.cageo.2016.10.002.
[15] J. Cordeiro, “Analysing Enterprise Ontology and Its Suitability for Model-Based Software Development,” vol. 2, pp. 257–269, 2019, doi: 10.1007/978-3-030-24854-3_19.
[16] M. A. Musa and M. S. Othman, “Knowledge map and enterprise ontology for enhancing business process reengineering in healthcare: A case of radiology department,” Int. J. Enterp. Inf. Syst., vol. 12, no. 2, pp. 26–46, 2016, doi: 10.4018/IJEIS.2016040103.
[17] توقعی، محسن و بهشت زاده کیایی، منیره و رضایی، سپیده،1395, “بررسی بکارگیری هستان شناسی در ساماندهی جریان دانش ضمنی سازمان,” in همایش ملی دانش و فناوری مهندسی برق، کامپیوتر و مکانیک ایران, 1395, vol. https://ci.
[18] A. M. Pinto-Llorente, M. C. Sánchez-Gómez, and A. Pedro Costa, “Qualitative and Mixed Methods Researches in Social Sciences,” ACM Int. Conf. Proceeding Ser., pp. 193–196, 2020, doi: 10.1145/3434780.3436696.
[19] A. Van Den Berg and M. Struwig, “Guidelines for Researchers Using an Adapted Consensual Qualitative Research Approach in... by Academic Conferences and publishing International - Issuu,” Electron. J. Bus. Res. Methods, vol. 15, no. 2, pp. 109–119, 2017.
[20] Y. Xiao and M. Watson, “Guidance on Conducting a Systematic Literature Review,” J. Plan. Educ. Res., vol. 39, pp. 93–112, 2019, doi: 10.1177/0739456X17723971.
[21] L. K. Nelson, “Computational Grounded Theory : A Methodological Framework,” Sociol. Methods Res., vol. 49, pp. 3–42, 2020, doi: 10.1177/0049124117729703.
[22] R. T. Webster, J. and Watson, “Analyzing the past to prepare for the future: Writing a literature review,” MIS Q., vol. 26, no. 2, pp. xiii–xxiii, 2002.
[23] K. Dal, S. Mendes, R. Cristina, and D. C. Pereira, “USE OF THE BIBLIOGRAPHIC REFERENCE MANAGER IN THE SELECTION OF PRIMARY STUDIES IN INTEGRATIVE REVIEWS,” Texto Context., vol. 28, pp. 1–13, 2019, doi: 10.1590/1980-265X-TCE-2017-0204.
[24] and A. S. Dermeval, Diego, Jéssyka Vilela, Ig Ibert Bittencourt, Jaelson Castro, Seiji Isotani, Patrick Brito, “Applications of ontologies in requirements engineering : a systematic review of the literature,” Requir. Eng., vol. 21, no. 4, pp. 405–437, 2016, doi: 10.1007/s00766-015-0222-6.
[25] M. Dadkhah, S. Araban, and S. Paydar, “A systematic literature review on semantic web enabled software testing,” J. Syst. Softw., vol. 162, p. 110485, 2020, doi: 10.1016/j.jss.2019.110485.
[26] J. Gharib, M., Giorgini, P. and Mylopoulos, “Towards an ontology for privacy requirements via a systematic literature review,” in 36th International Conference on Conceptual Modeling (ER), 2017, vol. 10650, pp. 193–208. doi: 10.1007/978-3-319-69904-2_16.
[27] F. Messaoudi, R., Mtibaa, A., Vacavant, A., Gargouri, F. and Jaziri, “Ontologies for Liver Diseases Representation : A Systematic Literature Review,” J. Digit. Imaging, pp. 1–11, 2019, doi: 10.1007/s10278-019-00303-2.
[28] H. wiesche, Manuel, Jurisch, Marlen C, Yetton, Philip W and Krcmar, “Grounded Theory Methodology in Information Systems Research,” MIS Q., vol. 41, no. 3, pp. 685–701, 2017, doi: 10.25300/MISQ/2017/41.3.02.
[29] L. & Guba, Competing Paradigms in Qualitative Research. 1994.
[30] J. E. Douglas and M. Bryon, “Interview data on severe behavioural eating difficulties in young children,” Arch. Dis. Child., vol. 75, no. 4, pp. 304–308, 1996, doi: 10.1136/adc.75.4.304.
[31] T. Hovorushchenko and O. Pavlova, Method of activity of ontology-based intelligent agent for evaluating initial stages of the software lifecycle, vol. 836. Springer International Publishing, 2019. doi: 10.1007/978-3-319-97885-7_17.
[32] V. R. Sampath Kumar et al., “Ontologies for industry 4.0,” Knowl. Eng. Rev., vol. 34, pp. 1–14, 2019, doi: 10.1017/S0269888919000109.