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Semantic Approach to Financial Knowledge Specification - Case of Emergency Policy Workflow

  • Jerzy Korczak
  • Helena Dudycz
  • Bartłomiej Nita
  • Piotr Oleksyk
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 311)

Abstract

The article presents an approach to integrate a business process knowledge in Decision Support Systems. The main research findings are related to the ontological and procedural issues of knowledge specification. The mathematical rigor used in process descriptions guarantees for precise definition of concepts and relationships in the domain knowledge. It concerns three major aspects of the system design, i.e. formalization of processes predefined in Business Process Modeling Notation, reuse of a domain ontology, and analysis of economic and financial information. Formally specified analytical processes and ontology allowed considerably minimize sources of ambiguity and confusion in the system design and implementation. The described approach is a continuation of the development of the intelligent cockpit for managers (InKoM project), whose main objective was to facilitate financial analysis and evaluation of economic status of the company. The current work and case studies are focused on specification of static (structural) and procedural knowledge of financial analysis in Small and Medium Enterprises. The content of the knowledge covers essential financial concepts and relationships related to the processes of emergency policy. An experiment has been carried out on real financial data extracted from the financial information system.

Keywords

Business Process Modeling Ontology Financial analysis Specification of processes Emergency policy 

Notes

Acknowledgement

The authors would like to thank Maurizio Proietti from National Research Council, IASI Rome, for his comments and assistance to run the analytical processes using BPAL platform.

References

  1. 1.
    Korczak, J., Dudycz, H., Nita, B., Oleksyk, P., Kaźmierczak, A.: Attempt to extend knowledge of decision support systems for small and medium-sized enterprises. In: Ganzha, M., Maciaszek, L., Paprzycki, M. (eds.) Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, vol. 8, pp. 1263–1271. Annals of Computer Science and Information Systems (2016).  https://doi.org/10.15439/2016f181
  2. 2.
    Beaver, W.H., Correia, M.: Financial Statement Analysis and the Prediction of Financial Distress. Now Publishers Inc., Breda (2011)Google Scholar
  3. 3.
    Altman, E.I., Hotchkiss, E.: Corporate Financial Distress and Bankruptcy: Predict and Avoid Bankruptcy, Analyze and Invest in Distressed Debt, 3rd edn. Wiley, Hoboken (2006)Google Scholar
  4. 4.
    Beck, T., Dermirguc-Kunt, A.: Small and medium-size enterprises: access to finance as a growth constraint. J. Bank. Financ. 30(11), 2931–2943 (2006)CrossRefGoogle Scholar
  5. 5.
    Smith, F., Proietti, M.: BPAL: a platform for managing semantically enriched conceptual process models. In: Cunningham, P., Cunningham, M. (eds.) eChallenges e-2014 Conference Proceedings IIMC International Information Management Corporation (2014)Google Scholar
  6. 6.
    De Nicola, A., Lezoche, M., Missikoff, M.: An ontological approach to business process modeling. In: 3th Indian International Conference on Artificial Intelligence, pp. 1794–1813 (2007)Google Scholar
  7. 7.
    O’Brien, T.J., Schmid, K.L., Hilliard, J.: Capital structure swaps and shareholder wealth. Eur. Financ. Manag. 13(5), 979–997 (2007)CrossRefGoogle Scholar
  8. 8.
    Aruldoss, M., Maladhy, D., Prasanna Venkatesan, V.: A framework for business intelligence application using ontological classification. Int. J. Eng. Sci. Technol. 3(2), 1213–1221 (2011)Google Scholar
  9. 9.
    Cheng, A., Lu, Y.-C., Sheu, C.: An ontology-based business intelligence application in financial knowledge management system. Expert Syst. Appl. 36(2), 3614–3622 (2009). Part 2CrossRefGoogle Scholar
  10. 10.
    Korczak, J., Dudycz, H., Dyczkowski, M.: Design of financial knowledge in dashboard for SME managers. In: Ganzha, M., Maciaszek, L., Paprzycki, M. (eds.) Proceedings of the 2013 Federated Conference on Computer Science and Information Systems, vol. 1, pp. 1111–1118. Annals of Computer Science and Information Systems (2013)Google Scholar
  11. 11.
    Neumayr, B., Schrefl, M., Linner, K.: Semantic cockpit: an ontology-driven, interactive business intelligence tool for comparative data analysis. In: De Troyer, O., Bauzer Medeiros, C., Billen, R., Hallot, P., Simitsis, A., Van Mingroot, H. (eds.) ER 2011. LNCS, vol. 6999, pp. 55–64. Springer, Heidelberg (2011).  https://doi.org/10.1007/978-3-642-24574-9_9 CrossRefGoogle Scholar
  12. 12.
    Dudycz, H., Korczak, J.: Process of ontology design for business intelligence system. In: Ziemba, E. (ed.) Information Technology for Management. LNBIP, vol. 243, pp. 17–28. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-30528-8_2 CrossRefGoogle Scholar
  13. 13.
    Dudycz, H., Korczak, J.: Conceptual design of financial ontology. In: Ganzha, M., Maciaszek, L., Paprzycki, M. (eds.) Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, vol. 5, pp. 1505–1511. Annals of Computer Science and Information Systems (2015).  https://doi.org/10.15439/978-83-60810-66-8
  14. 14.
    Abramowicz, W., Filipowska, A., Kaczmarek, M., Kaczmarek, T.: Semantically enhanced business process modeling notation. In: Smolnik, S., Teuteberg, F., Thomasal, O. (eds.) Semantic Technologies for Business and Information Systems Engineering: Concepts and Applications, pp. 259–275 (2012)Google Scholar
  15. 15.
    Martin, D., et al.: OWL-S: semantic markup for web services. W3C Member Submission (2004). http://www.w3.org/Submission/OWL-S/
  16. 16.
    Born, M., Filipowska, A., Kaczmarek, M., Markovic, I., Starzecka, M.: Business functions ontology and its application in semantic business process modeling. In: Proceedings of the ACIS, pp. 136–145 (2008)Google Scholar
  17. 17.
    Fensel, D., Lausen, H., Polleres, A., de Bruijn, J., Stollberg, M., Roman, D., Domingue, J.: Enabling Semantic Web Services: The Web Service Modeling Ontology. Springer, Heidelberg (2007).  https://doi.org/10.1007/978-3-540-34520-6 CrossRefGoogle Scholar
  18. 18.
    Calvanese, D., De Giacomo, G., Lembo, D., Montali, M., Santoso, A.: Ontology-based governance of data-aware processes. In: Krötzsch, M., Straccia, U. (eds.) RR 2012. LNCS, vol. 7497, pp. 25–41. Springer, Heidelberg (2012).  https://doi.org/10.1007/978-3-642-33203-6_4 CrossRefGoogle Scholar
  19. 19.
    Smith, F., Proietti, M.: Rule-based behavioral reasoning on semantic business processes. In: Proceedings of the 5th International Conference on Agents and Artificial Intelligence, pp. 130–143. SciTePress (2013)Google Scholar
  20. 20.
    Smith, F., Proietti, M.: Ontology-based representation and reasoning on process models: a logic programming approach (2014). https://arxiv.org/abs/1410.1776
  21. 21.
    Cagetti, M., De Nardi, M.: Entrepreneurship, frictions, and wealth. J. Polit. Econ. 114, 835–870 (2006)CrossRefGoogle Scholar
  22. 22.
    Coates J.C.: Mergers, acquisitions and restructuring: types, regulation, and patterns of practice. In: Oxford Handbook on Corporate Law and Governance. Discussion paper no. 781 (2014, Forthcoming)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Jerzy Korczak
    • 1
  • Helena Dudycz
    • 1
  • Bartłomiej Nita
    • 1
  • Piotr Oleksyk
    • 1
  1. 1.Wrocław University of EconomicsWrocławPoland

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