Abstract
Expert networks that are the community of professionals have become more popular in/over the last years. The paper presents a method of human community forming in expert network for joint task solving that is based on competence management approach. Related work analysis has been implemented and the requirements for the method development have been identified. The proposed method allows user to find the best possible community of experts for the reasonable time that is related to the number of experts and the number of skills in the competence management system.
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References
Smirnov, A., Kashevnik, A., Balandin, S., Baraniuc, O., Parfenov V.: Competency management system for technopark residents: smart space-based approach. In: Internet of Things, Smart Spaces, and Next Generation Networks and Systems. LNCS, vol. 9870, pp. 15–24 (2016). https://doi.org/10.1007/978-3-319-46301-8_2
Brumsteyn, Y.M., Dudikov, I.A.: Optimization of personnel distribution between organizations divisions on the basis of competence approach. Casp. J. Manag. High Technol. 2, 45–58 (2015)
Brumsteyn, Y.M., Dudikov, I.A.: Optimization models of resources selection for management of the project sets taking into account the dependence of the quality results, risks and expenses. Vestn. AGTU. Ser. Manag. Comput. Sci. Inform. 1, 78–89 (2015)
Orlovskiy, N.M.: Research of mathematical model for optimum plans formation of experts group functioning. Mod. Probl. Sci. Educ. 3, 128 (2014)
Yalçındağ, S., Cappanera, P., Scutellà , M.G., Şahin, E., Matta, A.: Pattern-based decompositions for human resource planning in home health care services. Comput. Oper. Res. 73, 12–26 (2016). https://doi.org/10.1016/j.cor.2016.02.011
Karimi-Majd, A., Mahootchi, M., Zakery, A.: A reinforcement learning methodology for a human resource planning problem considering knowledge-based promotion. Simul. Model. Pract. Theory 79, 87–99 (2017). https://doi.org/10.1016/j.simpat.2015.07.004
Touat, M., Bouzidi-Hassini, S., Benbouzid-Sitayeb, F., Benhamou, B.: A hybridization of genetic algorithms and fuzzy logic for the single-machine scheduling with flexible maintenance problem under human resource constraints. Appl. Soft Comput. 59, 556–573 (2017). https://doi.org/10.1016/j.asoc.2017.05.058
Zhang, L.: An inverse optimization model for human resource allocation problem considering competency disadvantage structure. Procedia Comput. Sci. 112, 1611–1622 (2017). https://doi.org/10.1016/j.procs.2017.08.248
Knyazeva, M., Bozhenyuk, A., Rozenberg, I.: Resource-constrained project scheduling approach under fuzzy conditions. Procedia Comput. Sci. 77, 56–64 (2015). https://doi.org/10.1016/j.procs.2015.12.359
Wi, H., Oh, S., Mun, J., Jung, M.: A team formation model based on knowledge and collaboration. Expert. Syst. Appl. Int. J. 36, 9121–9134 (2009). https://doi.org/10.1016/j.eswa.2008.12.031
Bohlouli, M., Mittas, N., Kakarontzas, G., Theodosiou, T., Angelis, L., Fathi, M.: Competence assessment as an expert system for human resource management: a mathematical approach. Expert Syst. Appl. 70, 83–102 (2016). https://doi.org/10.1016/j.eswa.2016.10.046
Tinelli, E., Colucci, S., Di Sciascio, E., Donini, F.: Knowledge compilation for automated team composition exploiting standard SQL. In: Proceeding SAC 2012 Proceedings of the 27th Annual ACM Symposium on Applied Computing, pp. 1680–1685 (2012)
Tinelli, E., Colucci, S., Donini, F., Di Sciascio, E., Giannini, S.: Embedding semantics in human resources management automation via SQL. Appl. Intell. 46, 1–31 (2016). https://doi.org/10.1007/s10489-016-0868-x
Rizvanov, D., Senkina, G.: Ontological approach to supporting decision-making management of the competencies of the organization. Vestn. RSREU 4, 79–84 (2009)
Li, C., Shan, M.: Team formation for generalized tasks in expertise social networks. In: IEEE Second International Conference on Social Computing (SocialCom), pp. 9–16 (2010). https://doi.org/10.1109/socialcom.2010.12
Liemhetcharat, S., Veloso, M.: Modeling and learning synergy for team formation with heterogeneous agents. In: AAMAS 2012 Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems, vol. 1, pp. 365–374 (2012)
Acknowledgements
The presented results are part of the research carried out within the project funded by grants # 16-29-12866 and # 18-37-00377 of the Russian Foundation for Basic Research, by the Russian State Research # 0073-2018-0002, and by ITMO University (Project #617038).
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Petrov, M., Kashevnik, A., Stepanenko, V. (2018). Competence-Based Method of Human Community Forming in Expert Network for Joint Task Solving. In: Alexandrov, D., Boukhanovsky, A., Chugunov, A., Kabanov, Y., Koltsova, O. (eds) Digital Transformation and Global Society. DTGS 2018. Communications in Computer and Information Science, vol 858. Springer, Cham. https://doi.org/10.1007/978-3-030-02843-5_3
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