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Novel profile’s selection algorithm using AI

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In order to better understand the job requirements, recruitment processes, and hiring processes it is needed to know the people skills. For a recruiter this entails analyzing and comparing the curricula of each available candidate and determining the most appropriate candidate that the activities that are required by the position. This process must be carried in the shortest length of time possible. In this paper, an algorithm is proposed to identify those candidates, either workers or college graduates.
Rocznik
Strony
18--32
Opis fizyczny
Bibliogr. 23 poz., fig., tab.
Twórcy
autor
  • Tecnológico Nacional de México/Instituto Tecnológico de Apizaco, 90300, Carretera Apizaco Tzompantepec, Esquina Av., Instituto Tecnológico S/N, Apizaco, Tlaxcala, México
  • Tecnológico Nacional de México/Instituto Tecnológico de Apizaco, 90300, Carretera Apizaco Tzompantepec, Esquina Av., Instituto Tecnológico S/N, Apizaco, Tlaxcala, México
  • Tecnológico Nacional de México/Instituto Tecnológico de Apizaco, 90300, Carretera Apizaco Tzompantepec, Esquina Av., Instituto Tecnológico S/N, Apizaco, Tlaxcala, México
  • Tecnológico Nacional de México/Instituto Tecnológico de Apizaco, 90300, Carretera Apizaco Tzompantepec, Esquina Av., Instituto Tecnológico S/N, Apizaco, Tlaxcala, México
  • Tecnológico Nacional de México/Instituto Tecnológico de Apizaco, 90300, Carretera Apizaco Tzompantepec, Esquina Av., Instituto Tecnológico S/N, Apizaco, Tlaxcala, México
  • Smartsoft America Business Applications S.A. de C.V., 90806, Adolfo López Mateos S/N, Texcacoac, Chiautempan, Tlaxcala, México
Bibliografia
  • [1] Baccour, L., Alimi, A., & John, R. (2014). Some notes on fuzzy similarity measures and application to classification of shapes, recognition of arabic sentences and mosaic. IAENG International Journal of Computer Science, 41(2), 81–90.
  • [2] Behara, K., Bhaskar, A., & Chung, E. (2018). Levenshtein distance for the structural comparison of od matrices. 40th Australasian Transport Research Forum (ATRF). Darwin.
  • [3] Bisandu, D., Prasad, R., & Liman, M. (2018). Clustering news articles using efficient similarity measure and n-grams. International Journal of Knowledge Engineering and Data Mining, 5(4), 333–348. doi:10.1504/IJKEDM.2018.095525
  • [4] Cheatham, M., & Hitzler, P. (2013). String similarity metrics for ontology alignment. International Semantic Web Conference, 8219, 294–309. doi: 10.1007/978-3-642-41338-419
  • [5] Deng, Y., Lei, H., Li, X., & Lin, Y. (2018). An improved deep neural network model for job matching. 2018 International Conference on Artificial Intelligence and Big Data (ICAIBD), 106-112. doi:10.1109/icaibd.2018.8396176
  • [6] Derous, E., & Fruyt, F. D. (2016). Developments in Recruitment and Selection Research. International Journal of Selection and Assessment, 24(1). doi:10.1111/ijsa.12123
  • [7] Dice, L. (1945). Measures of the amount of ecologic association between species. Ecology, 26(3), 297–302. doi:10.2307/1932409
  • [8] Esch, P., & Mente, M. (2018). Marketing video-enabled social media as part of your e-recruitment strategy: Stop trying to be trendy. Journal of Retailing and Consumer Services, 44, 266–273. doi:10.1016/j.jretconser.2018.06.016
  • [9] Esch, P., Black, J., & Ferolie, J. (2019). Marketing AI recruitment: The next phase in job application and selection. Computers in Human Behavior, 90, 215-222. doi:10.1016/j.chb.2018.09.009
  • [10] Gali, N., Mariescu-Istodor, R., Hostettler, D., & Fränti, P. (2019). Framework for syntactic string similarity measures. Expert Systems with Applications, 129, 169–185. doi:10.1016/j.eswa.2019.03.048
  • [11] González-Eras, A., & Aguilar, J. (2019). Determination of Professional Competencies Using an Alignment Algorithm of Academic Profiles and Job Advertisements Based on Competence Thesauri and Similarity Measures. International Journal of Artificial Intelligence in Education, 29(4), 536–567.
  • [12] Guo, X., Jerbi, H., & O’Mahony, M. (2014). An analysis framework for content-based job recommendation. In International Conference on Case-Based Reasoning 2014. Cork, Ireland.
  • [13] Huang, A. (2008). Similarity measures for text document clustering. New Zealand Computer Science Research Student Conference, 6, 49–56.
  • [14] I´m Talenty (n.d.). Intelligent platform for entailment student. Retrieved January 10, 2019 from https://imtalenty.com/login.xhtml
  • [15] Kerzendorf, W. (2019). Knowledge discovery through text-based similarity searches for astronomy literature. Journal of Astrophysics and Astronomy, 40, 1–7. doi:10.1007/s12036-019-9590-5
  • [16] Kessler, R., Béchet, N., Roche, M., Torres-Moreno, J., & El-Bèze, M. (2012). A hybrid approach to managing job offers and candidates. Information Processing and Management, 48, 1124–1135. doi:10.1016/j.ipm.2012.03.002
  • [17] Kondrak, G. (2005). N-gram similarity and distance. String Processing and Information Retrieval, 12, 115–126. doi:10.1007/11575832_13
  • [18] Liu, Y., Qin, K., Rao, C., & Mahamadu, M. (2017). Object-parameter approaches to predicting unknown data in an incomplete fuzzy soft set. International Journal of Applied Mathematics and Computer Science, 27(1), 157–167. doi:10.1515/amcs-2017-0011
  • [19] Pappis, C., & Karacapilidis, N. (1993). A comparative assessment of measures of similarity of fuzzy values. Fuzzy Sets and Systems, 56(2), 171–174. doi:10.1016/0165-0114(93)90141-4
  • [20] Porter, M. (1980). An algorithm for suffix stripping. Program, 40, 211–218.
  • [21] Sandhya, N., Lalitha, Y., Govardhan, A., & Anuradha, K. (2008). Analysis of similarity measures for text clustering. Computer Science Journals, 2(4), 1–10.
  • [22] Sedgewick, R., & Wayne, K. (2011). Algorithms, 4th Edition (pp. 244–336). Princenton.
  • [23] Shakya, A., & Paudel, S. (2019). Job-Candidate Matching using ESCO Ontology. Journal of the Institute of Engineering, 15(1), 1–13.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-012034d0-0b37-4dc6-ac1e-2f816624c9f6
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