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Using Cognitive Agents for Unstructured Knowledge Management in a Business Organization’s Integrated Information System

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Intelligent Information and Database Systems (ACIIDS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9621))

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Abstract

Management of unstructured knowledge in business organizations, mainly by using integrated information system, is a very important process. This type of knowledge allows supporting decision-making process to a high degree. The aim of this paper is to present using a cognitive agent’s architecture for knowledge management in integrated information system running in business organization. Analysis of the existing works in considered field is presented in the first part of paper; next an unstructured knowledge management process using The Learning Intelligent Distribution Agent architecture has been described. The last part of paper presents the research experiment performed in order to verification developed solution.

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References

  1. Franklin, S., Patterson, F.G.: The LIDA architecture: adding new modes of learning to an intelligent, autonomous, software agent. In: Proceedings of the International Conference on Integrated Design and Process Technology, Society for Design and Process Science, San Diego, CA (2006)

    Google Scholar 

  2. Hecker, A.: Knowledge beyond the individual? making sense of a notion of collective knowledge in organization theory. Organ. Stud. 33(3), 423–445 (2012)

    Article  Google Scholar 

  3. Hernes, M.: Performance evaluation of the customer relationship management agent’s in a cognitive integrated management support system. In: Nguyen, N.T. (ed.) Transactions on CCI XVIII. LNCS, vol. 9240, pp. 86–104. Springer, Heidelberg (2015)

    Chapter  Google Scholar 

  4. Maleszka, M., Nguyen, N.T.: Integration computing and collective intelligence. Expert Syst. Appl. 42(1), 358–378 (2015)

    Article  Google Scholar 

  5. Nguyen, N.T.: Inconsistency of knowledge and collective intelligence. Cybern. Syst. 39(6), 542–562 (2008)

    Article  MATH  Google Scholar 

  6. Pham, L.V., Pham, S.B.: Information extraction for Vietnamese real estate advertisements. In: Fourth International Conference on Knowledge and Systems Engineering (KSE), Danang (2012)

    Google Scholar 

  7. Sebastiani, F.: Machine learning in automated text categorization. ACM Comput. Surv. (CSUR) 34(1), 1–47 (2002)

    Article  Google Scholar 

  8. Tomassen, S.L.: Semi-automatic generation of ontologies for knowledge-intensive CBR. Norwegian University of Science and Technology (2002)

    Google Scholar 

  9. Tran, C.: Cognitive information processing. Vietnam J. Comput. Sci. 1, 207–218 (2014)

    Article  Google Scholar 

  10. Trandabăţ, D.: Using semantic roles to improve summaries. In: Proceedings of the 13th European Workshop on Natural Language Generation (ENLG 2011), Association for Computational Linguistics, Stroudsburg, PA, USA, pp. 164–169 (2011)

    Google Scholar 

  11. Vlas, R.E., Robinson, W.N.: Two rule-based natural language strategies for requirements discovery and classification in open source software development projects. J. Manage. Inf. Syst. 28(4), 11–38 (2012)

    Article  Google Scholar 

  12. Wawer, A.: Mining opinion attributes from texts using multiple kernel learning. In: IEEE 11th International Conference on Data Mining Workshops (2011)

    Google Scholar 

  13. Owoc, M., Weichbroth, P.: Validation model for discovered web user navigation patterns. In: Mercier-Laurent, E., Boulanger, D. (eds.) AI4KM 2012. IFIP AICT, vol. 422, pp. 38–52. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  14. Wilson, T., Wiebe, J., Hoffmann, P.: Recognizing contextual polarity: An exploration of features for phrase-level sentiment analysis. Comput. linguist. 35(3), 399–433 (2009)

    Article  Google Scholar 

  15. Zhang, C., Zhang, X., Jiang, W., Shen, Q., Zhang, S.: Rule-based extraction of spatial relations in natural language text. In: International Conference on Computational Intelligence and Software Engineering (2009)

    Google Scholar 

  16. Duch, W., Oentaryo, R.J, Pasquier, M.: Cognitive architectures: where do we go from here? In: Wang, P., Goertzel, P., Franklin, S. (eds.) Frontiers in Artificial Intelligence and Applications, Vol. 171, pp. 122–136. IOS Press (2008)

    Google Scholar 

  17. Korczak, J., Hernes, M., Bac, M.: Risk avoiding strategy in multi-agent trading system. In: Proceedings of Federated Conference Computer Science and Information Systems (FedCSIS), pp. 1119–1126 (2013)

    Google Scholar 

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Acknowledgement

This research was financially supported by the National Science Center (decision No. DEC-2013/11/D/HS4/04096).

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Authors and Affiliations

  1. Wrocław University of Economics ul, Komandorska 118/120, 53-345, Wrocław, Poland

    Marcin Hernes

Authors
  1. Marcin Hernes
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Correspondence to Marcin Hernes .

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Editors and Affiliations

  1. Wrocław University of Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Wrocław University of Technology, Wrocław, Poland

    Bogdan Trawiński

  3. Iwate Prefectural University, Takizawa, Japan

    Hamido Fujita

  4. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

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Hernes, M. (2016). Using Cognitive Agents for Unstructured Knowledge Management in a Business Organization’s Integrated Information System. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49381-6_33

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  • DOI: https://doi.org/10.1007/978-3-662-49381-6_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49380-9

  • Online ISBN: 978-3-662-49381-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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