A NOVEL PROFILE’S SELECTION ALGORITHM USING AI

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.
  Google Scholar

Behara, K., Bhaskar, A., & Chung, E. (2018). Levenshtein distance for the structural comparison of od matrices. 40th Australasian Transport Research Forum (ATRF). Darwin.
  Google Scholar

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. https://doi.org/10.1504/IJKEDM.2018.095525
DOI: https://doi.org/10.1504/IJKEDM.2018.095525   Google Scholar

Cheatham, M., & Hitzler, P. (2013). String similarity metrics for ontology alignment. International Semantic Web Conference, 8219, 294–309. https://doi.org/10.1007/978-3-642-41338-419
DOI: https://doi.org/10.1007/978-3-642-41338-4_19   Google Scholar

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. https://doi.org/10.1109/icaibd.2018.8396176
DOI: https://doi.org/10.1109/ICAIBD.2018.8396176   Google Scholar

Derous, E., & Fruyt, F. D. (2016). Developments in Recruitment and Selection Research. International Journal of Selection and Assessment, 24(1). https://doi.org/10.1111/ijsa.12123
DOI: https://doi.org/10.1111/ijsa.12123   Google Scholar

Dice, L. (1945). Measures of the amount of ecologic association between species. Ecology, 26(3), 297–302. https://doi.org/10.2307/1932409
DOI: https://doi.org/10.2307/1932409   Google Scholar

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. https://doi.org/10.1016/j.jretconser.2018.06.016
DOI: https://doi.org/10.1016/j.jretconser.2018.06.016   Google Scholar

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. https://doi.org/10.1016/j.chb.2018.09.009
DOI: https://doi.org/10.1016/j.chb.2018.09.009   Google Scholar

Gali, N., Mariescu-Istodor, R., Hostettler, D., & Fränti, P. (2019). Framework for syntactic string similarity measures. Expert Systems with Applications, 129, 169–185. https://doi.org/10.1016/j.eswa.2019.03.048
DOI: https://doi.org/10.1016/j.eswa.2019.03.048   Google Scholar

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.
DOI: https://doi.org/10.1007/s40593-019-00185-z   Google Scholar

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.
  Google Scholar

Huang, A. (2008). Similarity measures for text document clustering. New Zealand Computer Science Research Student Conference, 6, 49–56.
  Google Scholar

I ́m Talenty (n.d.). Intelligent platform for entailment student. Retrieved January 10, 2019 from https://imtalenty.com/login.xhtml
  Google Scholar

Kerzendorf, W. (2019). Knowledge discovery through text-based similarity searches for astronomy literature. Journal of Astrophysics and Astronomy, 40, 1–7. https://doi.org/10.1007/s12036-019-9590-5
DOI: https://doi.org/10.1007/s12036-019-9590-5   Google Scholar

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. https://doi.org/10.1016/j.ipm.2012.03.002
DOI: https://doi.org/10.1016/j.ipm.2012.03.002   Google Scholar

Kondrak, G. (2005). N-gram similarity and distance. String Processing and Information Retrieval, 12, 115–126. doi:10.1007/11575832_13
DOI: https://doi.org/10.1007/11575832_13   Google Scholar

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. https://doi.org/10.1515/amcs-2017-0011
DOI: https://doi.org/10.1515/amcs-2017-0011   Google Scholar

Pappis, C., & Karacapilidis, N. (1993). A comparative assessment of measures of similarity of fuzzy values. Fuzzy Sets and Systems, 56(2), 171–174. https://doi.org/10.1016/0165-0114(93)90141-4
DOI: https://doi.org/10.1016/0165-0114(93)90141-4   Google Scholar

Porter, M. (1980). An algorithm for suffix stripping. Program, 40, 211–218.
DOI: https://doi.org/10.1108/00330330610681286   Google Scholar

Sandhya, N., Lalitha, Y., Govardhan, A., & Anuradha, K. (2008). Analysis of similarity measures for text clustering. Computer Science Journals, 2(4), 1–10.
  Google Scholar

Sedgewick, R., & Wayne, K. (2011). Algorithms, 4th Edition (pp. 244–336). Princenton.
  Google Scholar

Shakya, A., & Paudel, S. (2019). Job-Candidate Matching using ESCO Ontology. Journal of the Institute of Engineering, 15(1), 1–13.
DOI: https://doi.org/10.3126/jie.v15i1.27699   Google Scholar