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Intelligent Method of Forming the HR Management Short-Term Project

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Advances in Intelligent Systems and Computing V (CSIT 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1293))

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Abstract

A method for forming a short-term HR project based on machine learning has been developed. The proposed method enables to reduce the HR time spent as well as the cost of recruiters. A paper presents a smart chatbot, which conducts an interview with a potential team member. Chatbot acts as an HR, which after the interview transmits data to the database and per each applicant. Parsing has increased the sample of applicants who have been submitted a request for chatbot interview. Based on the obtained data, the chatbot analyzes the machine learning method and displays the optimal result on the distribution of roles in the team among the best applicants.

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References

  1. Comendador, B.E.V., Francisco, B.M.B., Medenilla, J.S., Mae, S.: Pharmabot: a pediatric generic medicine consultant chatbot. J. Autom. Control Eng. 3(2), 137–140 (2015)

    Article  Google Scholar 

  2. Zhou, L., Gao, J., Li, D., Shum, H.Y.: The design and implementation of XiaoIce, an empathetic social chatbot. Comput. Linguist. 46(1), 53–93 (2020)

    Article  Google Scholar 

  3. Fryer, L.K., Nakao, K., Thompson, A.: Chatbot learning partners: connecting learning experiences, interest and competence. Comput. Hum. Behav. 93, 279–289 (2019). https://doi.org/10.1016/j.chb.2018.12.023

    Article  Google Scholar 

  4. Mathew, R.B., Varghese, S., Joy S.E., Alex, S.S.: Chatbot for disease prediction and treatment recommendation using machine learning. In: Proceedings of the 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI), Tirunelveli, India, pp. 851–856 (2019). https://doi.org/10.1109/icoei.2019.8862707

  5. Rajender Kumar Surana, C.S., Shriya, Gupta D.B., Shankar, S.P.: Intelligent chatbot for requirements elicitation and classification. In: Proceedings of the 2019 4th International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT), Bangalore, India, pp. 866–870 (2019). https://doi.org/10.1109/rteict46194.2019.9016907

  6. Ndukwe, I.G., Daniel, B.K., Amadi, C.E.: A machine learning grading system using chatbots. In: Artificial Intelligence in Education. LNCS, pp. 365-368. Springer (2019). https://doi.org/10.1007/978-3-030-23207-8_67

  7. Sheikh, S.A., Tiwari, V., Singhal, S.: Generative model chatbot for Human Resource using Deep Learning. In: Proceedings of the 2019 International Conference on Data Science and Engineering (ICDSE), Patna, India, pp. 126–132 (2019). https://doi.org/10.1109/icdse47409.2019.8971795

  8. Zhukovska, V.M.: Digital technologies in personnel management: essence, tendencies, development. Sci. Bull. Int. Human. Univ. Ser. Econ. Manag. 27(2), 13–17 (2017). (in Ukrainian)

    Google Scholar 

  9. Xu, Z., Song, B.: A machine learning application for human resource data mining problem. In: LNCS, pp. 847–856. Springer (2006). https://doi.org/10.1007/11731139_99

  10. Wang, Q., Li, B., Hu, J.: Feature selection for human resource selection based on affinity propagation and SVM sensitivity analysis. In: Proceedings of the 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), pp. 31–36 (2009). https://doi.org/10.1109/nabic.2009.5393596

  11. Tomassen, M.E.: Exploring the black box of machine learning in human resource management: an HR perspective on the consequences for HR professionals. Master’s thesis. University of Twente (2016)

    Google Scholar 

  12. Cui, L., Huang, S., Wei, F., Tan, C., Duan, C., Zhou, M.: SuperAgent: a customer service chatbot for e-commerce websites. In: Proceedings of the Association for Computational Linguistics, ACL 2017, System Demonstrations, pp. 97–102 (2017)

    Google Scholar 

  13. Nuruzzaman, M., Hussain, O.K.: A survey on chatbot implementation in customer service industry through deep neural networks. In: Proceedings of the 2018 IEEE 15th International Conference on e-Business Engineering (ICEBE), Xi’an, pp. 54–61 (2018). https://doi.org/10.1109/icebe.2018.00019

  14. Nuruzzaman, M., Hussain, O.K.: IntelliBot: a dialogue-based chatbot for the insurance industry. Knowl.-Based Syst. 196, 105810 (2020). https://doi.org/10.1016/j.knosys.2020.105810

    Article  Google Scholar 

  15. Necula, S.-C., Strîmbei, C.: People analytics of semantic web human resource résumés for sustainable talent acquisition. Sustainability 11(13), 3520 (2019). https://doi.org/10.3390/su11133520

    Article  Google Scholar 

  16. Lunsford, D.L.: An output model for human resource development analytics. Perform. Improv. Q. 32(1), 13–35 (2019). https://doi.org/10.1002/piq.21284

    Article  Google Scholar 

  17. Long, Y., Liu, J., Fang, M., Wang, T., Jiang, W.: Prediction of employee promotion based on personal basic features and post features. In: Proceedings of the International Conference on Data Processing and Applications – ICDPA 2018, pp. 5–10 (2018). https://doi.org/10.1145/3224207.3224210

  18. Dialogflow. https://dialogflow.com/

  19. Liebenberg, J., Huisman, M., Mentz, E.: Knowledge and skills requirements for software developer students. Int. J. Soc. Behav. Educ. Econ. Bus. Ind. Eng. 8(8), 2604–2609 (2014)

    Google Scholar 

  20. Ivonina, A.I., Chulanova, O.L., Davletshina, YuM: Modern areas of theoretical and methodological developments in the field of management: the role of soft-skills and hard skills in the professional and career development of employees. Bull. Eurasian Sci. 9(1), 1–18 (2017). (in Russian)

    Google Scholar 

  21. Chuang, Z., Ming, W., Guang, L.C., Bo, X., Zhi-qing, L.: Resume parser: semi-structured Chinese document analysis. In: Proceedings of the 2009 WRI World Congress on Computer Science and Information Engineering, pp. 12–16 (2009). https://doi.org/10.1109/csie.2009.562

  22. Celik, D., Karakas, A., Bal, G., Gultunca, C., Elci, A., Buluz, B., Alevli, M.C.: Towards an information extraction system based on ontology to match resumes and jobs. In: Proceedings of the 2013 IEEE 37th Annual Computer Software and Applications Conference Workshops, pp. 333–338 (2013). https://doi.org/10.1109/compsacw.2013.60

  23. Wentan, Y., Yupeng, Q.: Chinese resume information extraction based on semi-structured text. In: Proceedings of the 2017 36th Chinese Control Conference (CCC), pp. 11177–11182 (2017). https://doi.org/10.23919/chicc.2017.8029141

  24. Das, P., Pandey, M., Rautaray, S.S.: A CV parser model using entity extraction process and big data tools. IJ Inf. Technol. Comput. Sci. 9, 21–31 (2018)

    Google Scholar 

  25. Tobing, B.C.L., Suhendra, I.R., Halim, C.: Catapa resume parser. In: Proceedings of the 2019 3rd International Conference on Natural Language Processing and Information Retrieval (NLPIR 2019), pp. 68–74 (2019). https://doi.org/10.1145/3342827.3342832

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Authors and Affiliations

  1. Ternopil National Economic University, Lvivska Str., 11, Ternopil, 46000, Ukraine

    Hrystyna Lipyanina, Oleg Sachenko, Taras Lendyuk, Anatoliy Sachenko & Nadiia Vasylkiv

Authors
  1. Hrystyna Lipyanina
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  2. Oleg Sachenko
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  3. Taras Lendyuk
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  4. Anatoliy Sachenko
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  5. Nadiia Vasylkiv
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Corresponding author

Correspondence to Anatoliy Sachenko .

Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Lviv Polytechnic National University, Lviv, Ukraine

    Natalya Shakhovska

  2. Institute of Computer Science and Information Technologies, Lviv Polytechnic National University, Lviv, Ukraine

    Mykola O. Medykovskyy

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Lipyanina, H., Sachenko, O., Lendyuk, T., Sachenko, A., Vasylkiv, N. (2021). Intelligent Method of Forming the HR Management Short-Term Project. In: Shakhovska, N., Medykovskyy, M.O. (eds) Advances in Intelligent Systems and Computing V. CSIT 2020. Advances in Intelligent Systems and Computing, vol 1293. Springer, Cham. https://doi.org/10.1007/978-3-030-63270-0_71

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