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The Intellectual System Development of Distant Competencies Analyzing for IT Recruitment

  • Antonii RzheuskyiEmail author
  • Orest Kutyuk
  • Orysia Voloshyn
  • Agnieszka Kowalska-Styczen
  • Viktor Voloshyn
  • Lyubomyr Chyrun
  • Sofiia Chyrun
  • Dmytro Peleshko
  • Taras Rak
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1080)

Abstract

AHP study methods of solving problems to use AHP comparing alternatives (TOPSIS) and supervised learning algorithm using linear regression are proposed. To meet the challenges these methods were chosen language PHP, its own established framework CollEntRes, additional tools that helped during the programming process to detect errors and correct them (Debug), popular modern framework to work with the client part Angular, relational control systems, databases MariaDB HeidiSQL and its client, the technology to work with the client part of the site HTML and CSS and additional tools such as Bootstrap and SCSS. As a result, within practical implementation of software tool has been developed whose main goal is an analysis of matrix distant for recruitment in IT sector. The software tool covers general information and requirements for software, described in detail basic functionality of the software analysis and test cases for all kinds of users is presented in the article.

Keywords

AHP TOPSIS Machine learning Distant Distance learning Competencies IT recruitment Intellectual system 

References

  1. 1.
  2. 2.
    Haugeland, J.: Programmer competency matrix. perspectives on software, technology and business. http://sijinjoseph.com/programmer-competency-matrix/
  3. 3.
    Abramson, D., Krishnamoorthy, M., Dang, H.: Simulated annealing cooling schedules for the school timetabling problem (1997). http://www.rdt.monash.edu.au/~davida/papers/cool.ps.Z
  4. 4.
    Shakhovska, N., Vysotska, V., Chyrun, L.: Intelligent systems design of distance learning realization for modern youth promotion and involvement in independent scientific researches. In: Advances in Intelligent Systems and Computing, vol. 512, pp. 175–198 (2017)Google Scholar
  5. 5.
    Shakhovska, N., Vysotska, V., Chyrun, L.: Features of E-learning realization using virtual research laboratory. In: Computer Science and Information Technologies, CSIT, pp. 143–148 (2016)Google Scholar
  6. 6.
    Bobalo, Y., Stakhiv, P., Mandziy, B., Shakhovska, N., Holoschuk, R.: The concept of electronic textbook “Fundamentals of theory of electronic circuits”. In: Przegląd Elektrotechniczny, 88 NR 3a/2012, pp. 16–18 (2012)Google Scholar
  7. 7.
    Lytvyn, V., Vysotska, V., Chyrun, L., Chyrun, L.: Distance learning method for modern youth promotion and involvement in independent scientific researches. In: Data Stream Mining & Processing (DSMP), pp. 269–274 (2016)Google Scholar
  8. 8.
    Lytvyn, V., Vysotska, V., Pukach, P., Bobyk, I., Pakholok, B.: A method for constructing recruitment rules based on the analysis of a specialist’s competences. Eastern Eur. J. Enterp. Technol. 6(2(84)), 4–14 (2016)Google Scholar
  9. 9.
    Chyrun, L., Kis, I., Vysotska, V., Chyrun, L.: Content monitoring method for cut formation of person psychological state in social scoring. In: International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT, pp. 106–112 (2018)Google Scholar
  10. 10.
    Chyrun, L., Vysotska, V., Kis, I., Chyrun, L.: Content analysis method for cut formation of human psychological state. In: International Conference on Data Stream Mining and Processing, pp. 139–144 (2018)Google Scholar
  11. 11.
    Kanishcheva, O., Vysotska, V., Chyrun, L., Gozhyj, A.: Method of integration and content management of the information resources network. In: Advances in Intelligent Systems and Computing, vol. 689, pp. 204–216. Springer (2017)Google Scholar
  12. 12.
    Kowalik, D., Rusyn, B.: Innovative vocation didactics aimed at the preparation of staff according to Industry 4.0 and Europe 2020. In: International Conference on Education Reform and Modern Management, pp. 12–17 (2017)Google Scholar
  13. 13.
    Vysotska, V., Burov, Y., Lytvyn, V., Oleshek, O.: Automated monitoring of changes in web resources. In: Lecture Notes in Computational Intelligence and Decision Making, vol. 1020, pp. 348–363 (2019)Google Scholar
  14. 14.
    Demchuk, A., Lytvyn, V., Vysotska, V., Dilai, M.: Methods and means of web content personalization for commercial information products distribution. In: Lecture Notes in Computational Intelligence and Decision Making, vol. 1020, pp. 332–347 (2019)Google Scholar
  15. 15.
    Lytvyn, V., Vysotska, V., Mykhailyshyn, V., Rzheuskyi, A., Semianchuk, S.: System development for video stream data analyzing. In: Lecture Notes in Computational Intelligence and Decision Making, vol. 1020, pp. 315–331 (2019)Google Scholar
  16. 16.
    Su, J., Sachenko, A., Lytvyn, V., Vysotska, V., Dosyn, D.: Model of touristic information resources integration according to user needs. In: Computer Sciences and Information Technologies, pp. 113–116 (2018)Google Scholar
  17. 17.
    Mukalov, P., Zelinskyi, O., Levkovych, R., Tarnavskyi, P., Pylyp, A., Shakhovska, N.: Development of system for auto-tagging articles, based on neural network. In: CEUR Workshop Proceedings, vol. 2362, pp. 116–125 (2019)Google Scholar
  18. 18.
    Shakhovska, N.B., Noha, R.Y.: Methods and tools for text analysis of publications to study the functioning of scientific schools. J. Autom. Inf. Sci. 47(12), 29–43 (2015)CrossRefGoogle Scholar
  19. 19.
    Arzubov, M., Shakhovska, N., Lipinski, P.: Analyzing ways of building user profile based on web surf history. In: CSIT, vol. 1, pp. 377–380 (2017)Google Scholar
  20. 20.
    Shakhovska, N., Shvorob, I.: The method for detecting plagiarism in a collection of documents. In: Computer Sciences and Information Technologies (CSIT), pp. 142–145 (2015)Google Scholar
  21. 21.
    Rusyn, B., Vysotska, V., Pohreliuk, L.: Model and architecture for virtual library information system. In: Computer Sciences and Information Technologies, pp. 37–41 (2018)Google Scholar
  22. 22.
    Rusyn, B., Lytvyn, V., Vysotska, V., Emmerich, M., Pohreliuk, L.: The virtual library system design and development. In: Advances in Intelligent Systems and Computing, vol. 871, pp. 328–349 (2019)Google Scholar
  23. 23.
    Lytvyn, V., Vysotska, V., Dosyn, D., Burov, Y.: Method for ontology content and structure optimization, provided by a weighted conceptual graph. Webology 15(2), 66–85 (2018)Google Scholar
  24. 24.
    Lytvyn, V., Peleshchak, I., Vysotska, V., Peleshchak, R.: Satellite spectral information recognition based on the synthesis of modified dynamic neural networks and holographic data processing techniques. In: International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT, pp. 330–334 (2018)Google Scholar
  25. 25.
    Gozhyj, A., Kalinina, I., Vysotska, V., Gozhyj, V.: The method of web-resources management under conditions of uncertainty based on fuzzy logic. In: International Scientific and Technical Conference on Computer Sciences and Information Technologies, pp. 343–346 (2018)Google Scholar
  26. 26.
    Gozhyj, A., Vysotska, V., Yevseyeva, I., Kalinina, I., Gozhyj, V.: Web resources management method based on intelligent technologies. In: Advances in Intelligent Systems and Computing, vol. 871, pp. 206–221 (2019)Google Scholar
  27. 27.
    Lytvyn, V., Vysotska, V., Dosyn, D., Lozynska, O., Oborska, O.: Methods of building intelligent decision support systems based on adaptive ontology. In: International Conference on Data Stream Mining and Processing, DSMP, pp. 145–150 (2018)Google Scholar
  28. 28.
    Burov, Y., Vysotska, V., Kravets, P.: Ontological approach to plot analysis and modeling. In: CEUR Workshop Proceedings, vol. 2362, pp. 22–31 (2019)Google Scholar
  29. 29.
    Lytvyn, V., Vysotska, V., Peleshchak, I., Rishnyak, I., Peleshchak, R.: Time dependence of the output signal morphology for nonlinear oscillator neuron based on Van der Pol Model. Int. J. Intell. Syst. Appl. 10, 8–17 (2018)Google Scholar
  30. 30.
    Lytvyn, V., Vysotska, V., Veres, O., Rishnyak, I., Rishnyak, H.: The risk management modelling in multi project environment. In: International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT, pp. 32–35 (2017)Google Scholar
  31. 31.
    Lytvyn, V., Vysotska, V., Pukach, P., Vovk, M., Ugryn, D.: Method of functioning of intelligent agents, designed to solve action planning problems based on ontological approach. Eastern Eur. J. Enterp. Technol. 3(2(87)), 11–17 (2017)Google Scholar
  32. 32.
    Vysotska, V., Lytvyn, V., Burov, Y., Gozhyj, A., Makara, S.: The consolidated information web-resource about pharmacy networks in city. In: CEUR Workshop Proceedings, vol. 2255, pp. 239–255 (2018)Google Scholar
  33. 33.
    Lytvyn, V., Kuchkovskiy, V., Vysotska, V., Markiv, O., Pabyrivskyy, V.: Architecture of system for content integration and formation based on cryptographic consumer needs. In: Conference on Computer Sciences and Information Technologies, CSIT, pp. 391–395 (2018)Google Scholar
  34. 34.
    Lytvyn, V., Vysotska, V., Kuchkovskiy, V., Bobyk, I., Malanchuk, O., Ryshkovets, Y., Pelekh, I., Brodyak, O., Bobrivetc, V., Panasyuk, V.: Development of the system to integrate and generate content considering the cryptocurrent needs of users. Eastern Eur. J. Enterp. Technol. 1(2–97), 18–39 (2019)Google Scholar
  35. 35.
    Lytvyn, V., Vysotska, V., Demchuk, A., Demkiv, I., Ukhanska, O., Hladun, V., Kovalchuk, R., Petruchenko, O., Dzyubyk, L., Sokulska, N.: Design of the architecture of an intelligent system for distributing commercial content in the internet space based on SEO-technologies, neural networks, and Machine Learning. Eastern Eur. J. Enterp. Technol. 2(2–98), 15–34 (2019)Google Scholar
  36. 36.
    Mukalov, P., Zelinskyi, O., Levkovych, R., Tarnavskyi, P., Pylyp,A., Shakhovska, N.: Development of system for auto-tagging articles, based on neural network. In: CEUR Workshop Proceedings, vol. 2362, pp. 106–115 (2019)Google Scholar
  37. 37.
    Shakhovska, N., Basystiuk, O., Shakhovska, K.: Development of the speech-to-text chatbot interface based on Google API. In: CEUR Workshop Proceedings, pp. 212–221 (2019)Google Scholar
  38. 38.
    Korobchinsky, M., Vysotska, V., Chyrun, L., Chyrun, L.: Peculiarities of content forming and analysis in internet newspaper covering music news. In: International Scientific and Technical Conference on Computer Sciences and Information Technologies, pp. 52–57 (2017)Google Scholar
  39. 39.
    Vysotska, V., Chyrun, L.: Analysis features of information resources processing. In: Proceedings of the International Conference on Computer Science and Information Technologies, CSIT, pp. 124–128 (2015)Google Scholar
  40. 40.
    Vysotska, V., Chyrun, L., Chyrun, L.: The Commercial content digest formation and distributional process. In: Proceedings of the XI-th International Conference on Computer Science and Information Technologies, CSIT 2016, pp. 186–189 (2016)Google Scholar
  41. 41.
    Su, J., Vysotska, V., Sachenko, A., Lytvyn, V., Burov, Y.: Information resources processing using linguistic analysis of textual content. In: Intelligent Data Acquisition and Advanced Computing Systems Technology and Applications, Romania, pp. 573–578 (2017)Google Scholar
  42. 42.
    Vysotska, V., Rishnyak, I., Chyrun L.: Analysis and evaluation of risks in electronic commerce. In: 9th International Conference on CAD Systems in Microelectronics, pp. 332–333 (2007)Google Scholar
  43. 43.
    Vysotska, V., Chyrun, L., Chyrun, L.: Information technology of processing information resources in electronic content commerce systems. In: Computer Science and Information Technologies, CSIT 2016, pp. 212–222 (2016)Google Scholar
  44. 44.
    Rzheuskyi, A., Gozhyj, A., Stefanchuk, A., Oborska, O., Chyrun, L., Lozynska, O., Mykich, K., Basyuk, T.: Development of mobile application for choreographic productions creation and visualization. In: CEUR Workshop Proceedings, vol. 2386, pp. 340–358 (2019)Google Scholar
  45. 45.
    Vasyl, L., Vysotska, V., Dosyn, D., Roman, H., Rybchak, Z.: Application of sentence parsing for determining keywords in Ukrainian texts. In: Computer Science and Information Technologies, CSIT, pp. 326–331 (2017)Google Scholar
  46. 46.
    Vysotska, V., Hasko, R., Kuchkovskiy, V.: Process analysis in electronic content commerce system. In: International Conference on Computer Sciences and Information Technologies, CSIT, pp. 120–123 (2015)Google Scholar
  47. 47.
    Vysotska, V., Fernandes, V.B., Emmerich, M.: Web content support method in electronic business systems. In: CEUR Workshop Proceedings, vol. 2136, pp. 20–41 (2018)Google Scholar
  48. 48.
    Lytvyn, V., Sharonova, N., Hamon, T., Vysotska, V., Grabar, N., Kowalska-Styczen, A.: Computational linguistics and intelligent systems. In: CEUR Workshop Proceedings, vol. 2136 (2018)Google Scholar
  49. 49.
    Lytvyn, V., Vysotska, V., Burov, Y., Demchuk, A.: Architectural ontology designed for intellectual analysis of E-tourism resources. In: International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT, pp. 335–338 (2018)Google Scholar
  50. 50.
    Lytvyn, V., Vysotska, V., Rzheuskyi, A.: Technology for the psychological portraits formation of social networks users for the IT specialists recruitment based on big five, NLP and Big Data analysis. In: CEUR Workshop Proceedings, vol. 2392, pp. 147–171 (2019)Google Scholar
  51. 51.
    Lytvyn, V., Vysotska, V., Rusyn, B., Pohreliuk, L., Berezin, P., Naum, O.: Textual content categorizing technology development based on ontology. In: CEUR Workshop Proceedings, vol. 2386, pp. 234–254 (2019)Google Scholar
  52. 52.
    Vysotska, V., Lytvyn, V., Burov, Y., Berezin, P., Emmerich, M., Basto Fernandes, V.: Development of information system for textual content categorizing based on ontology. In: CEUR Workshop Proceedings, vol. 2362, pp. 53–70 (2019)Google Scholar
  53. 53.
    Zdebskyi, P., Vysotska, V., Peleshchak, R., Peleshchak, I., Demchuk, A., Krylyshyn, M.: An application development for recognizing of view in order to control the mouse pointer. In: CEUR Workshop Proceedings, vol. 2386, pp. 55–74 (2019)Google Scholar
  54. 54.
    Kaminskyi, R., Kunanets, N., Pasichnyk, V., Rzheuskyi, A., Khudyi, A.: Recovery gaps in experimental data. In: CEUR Workshop Proceedings, vol. 2136, pp. 170–179 (2018)Google Scholar
  55. 55.
    Kazarian, A., Holoshchuk, R., Kunanets, N., Shestakevysh, T., Rzheuskyi, A.: Information support of scientific researches of virtual communities on the platform of cloud services. In: Advances in Intelligent Systems and Computing III, vol. 871, pp. 301–311 (2018)Google Scholar
  56. 56.
    Rzheuskyi, A., Kunanets, N., Stakhiv, M.: Recommendation system virtual reference. In: Computer Sciences and Information Technologies (CSIT), pp. 203–206 (2018)Google Scholar
  57. 57.
    Kaminskyi, R., Kunanets, N., Rzheuskyi, A., Khudyi, A.: Methods of statistical research for information managers. In: International Scientific and Technical Conference on Computer Sciences and Information Technologies, pp. 127–131 (2018)Google Scholar
  58. 58.
    Tomashevskyi, V., Yatsyshyn, A., Pasichnyk, V., Kunanets, N., Rzheuskyi, A.: Data warehouses of hybrid type: features of construction. In: Advances. In Intelligent Systems and Computing, pp. 325–334 (2019)Google Scholar
  59. 59.
    Rzheuskyi, A., Matsuik, H., Veretennikova, N., Vaskiv, R.: Selective dissemination of information – technology of information support of scientific research. In: Advances in Intelligent Systems and Computing III, vol. 871, pp. 235–245 (2019)Google Scholar
  60. 60.
    Naum, O., Chyrun, L., Kanishcheva, O., Vysotska, V.: Intellectual system design for content formation. In: Proceedings of the International Conference on Computer Science and Information Technologies, CSIT, pp. 131–138 (2017)Google Scholar
  61. 61.
    Lytvyn, V., Vysotska, V., Burov, Y., Veres, O., Rishnyak, I.: The contextual search method based on domain thesaurus. In: Advances in Intelligent Systems and Computing, vol. 689, pp. 310–319 (2018)Google Scholar
  62. 62.
    Lytvyn, V., Pukach, P., Bobyk, I., Vysotska, V.: The method of formation of the status of personality understanding based on the content analysis. Eastern-European Journal of Enterprise Technologies 5(2(83)), 4–12 (2016)Google Scholar
  63. 63.
    Lytvyn, V., Vysotska, V., Veres, O., Rishnyak, I., Rishnyak, H.: Classification methods of text documents using ontology based approach. In: Advances in Intelligent Systems and Computing, vol. 512, pp. 229–240 (2017)Google Scholar
  64. 64.
    Lytvyn, V., Vysotska, V, Veres, O., Rishnyak, I., Rishnyak, H.: Content linguistic analysis methods for textual documents classification. In: Proceedings of the XI-th International Conference on Computer Science and Information Technologies, CSIT 2016, pp. 190–192 (2016)Google Scholar
  65. 65.
    Kochan, R., Lee, K., Kochan, V., Sachenko, A.: Development of a dynamically reprogrammable NCAP. In: Proceedings of the IEEE Instrumentation and Measurement Technology Conference, pp. 1188–1193 (2004)Google Scholar
  66. 66.
    Hiromoto, R.E., Sachenko, A., Kochan, V., Koval, V., Turchenko, V., Roshchupkin, O., Yatskiv, V., Kovalok, K.: Mobile ad hoc wireless network for pre- and post-emergency situations in nuclear power plant. In: Proceedings of the 2nd IEEE International Symposium on Wireless Systems within the Conferences on Intelligent Data Acquisition and Advanced Computing Systems, pp. 92–96 (2014)Google Scholar
  67. 67.
    Lytvynenko, V., Wojcik, W., Fefelov, A., Lurie, I., Savina, N., Voronenko, M., et al.: Hybrid methods of GMDH-neural networks synthesis and training for solving problems of time series forecasting. In: Lecture Notes in Computational Intelligence and Decision Making, vol. 1020, pp. 513–531 (2019)Google Scholar
  68. 68.
    Babichev, S., Durnyak, B., Pikh, I., Senkivskyy, V.: An evaluation of the objective clustering inductive technology effectiveness implemented using density-based and agglomerative hierarchical clustering algorithms. In: Lecture Notes in Computational Intelligence and Decision Making, vol. 1020, pp. 532–553 (2019)Google Scholar
  69. 69.
    Bidyuk, P., Gozhyj, A., Kalinina, I.: Probabilistic inference based on LS-method modifications in decision making problems. In: Lecture Notes in Computational Intelligence and Decision Making, vol. 1020, pp. 422–433 (2019)Google Scholar
  70. 70.
    Vysotska, V.: Linguistic analysis of textual commercial content for information resources processing. In: Modern Problems of Radio Engineering, Telecommunications and Computer Science, TCSET 2016, pp. 709–713 (2016)Google Scholar
  71. 71.
    Lytvyn, V., Vysotska, V.: Designing architecture of electronic content commerce system. In: Computer Science and Information Technologies, CSIT 2015, pp. 115–119 (2015)Google Scholar
  72. 72.
    Veres, O., Rusyn, B., Sachenko, A., Rishnyak, I.: Choosing the method of finding similar images in the reverse search system. In: CEUR Workshop Proceedings, pp. 99–107 (2018)Google Scholar
  73. 73.
    Mukalov, P., Zelinskyi, O., Levkovych, R., Tarnavskyi, P., Pylyp, A., Shakhovska, N.: Development of system for auto-tagging articles, based on neural network. In: CEUR Workshop Proceedings, vol. 2362, pp. 106–115 (2019)Google Scholar
  74. 74.
    Basyuk, T.: The main reasons of attendance falling of internet resource. In: Proceedings of the X-th International Conference on Computer Science and Information Technologies, CSIT 2015, pp. 91–93 (2015)Google Scholar
  75. 75.
    Rzheuskyi, A., Kutyuk, O., Vysotska, V., Burov, Ye., Lytvyn, V., Chyrun, L.: The architecture of distant competencies analyzing system for IT recruitment In: Proceedings of International Scientific Conference “Computer sciences and information technologies” (CSIT-2019), IEEE v. 3, pp. 254–261 (2019)Google Scholar

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Authors and Affiliations

  1. 1.Lviv Polytechnic National UniversityLvivUkraine
  2. 2.Silesian University of TechnologyGliwicePoland
  3. 3.IT STEP UniversityLvivUkraine

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