APPLYING INTELLIGENT TECHNIQUES FOR TALENT RECRUITMENT
Isaac FLORES-HERNÁNDEZ
isaac_camus@hotmail.comInstituto Tecnológico de Apizaco, Computer Systems Department, Fco I Madero, Barrio de San José, 90300 Apizaco, Tlaxcala (Mexico)
Edmundo BONILLA-HUERTA
Instituto Tecnológico de Apizaco, Computer Systems Department, Fco I Madero, Barrio de San José, 90300 Apizaco, Tlaxcala (Mexico)
Perfecto MALAQUIAS QUINTERO-FLORES
* Instituto Tecnológico de Apizaco, Computer Systems Department, Fco I Madero, Barrio de San José, 90300 Apizaco, Tlaxcala (Mexico)
Oscar Atriano PONCE
Smartsoft America BA, Calle Adolfo López Mateos, Texcacoac, 90806 Chiautempan (Mexico)
José Crispín HERNÁNDEZ-HERNÁNDEZ
Instituto Tecnológico de Apizaco, Computer Systems Department, Fco I Madero, Barrio de San José, 90300 Apizaco, Tlaxcala (Mexico)
Abstract
The objective of this research is to describe a system to aligned the hard and soft skills of the applicant to the current labor market. For this, a system was implemented which uses Web Scraping to get a general profile of an area, meanwhile for the evaluation of the applicant soft skills is used a Test Cleaver and for the hard skills fuzzy inference system is implemented. Therefore, the data is entered into an Analytic Hierarchy Process, with this, the applier is able to see which area is better to improve according to the hard and soft skills.
Keywords:
Fuzzy logic, Web scraping, Personnel Selection, AHPReferences
Algur, S., Bhat, P., & Kulkarni, N. (2016). Educational Data Mining: Classification Techniques for Recruitment Analysis. International Journal of Modern Education and Computer Science (IJMECS), 8(2), 59–65. https://doi.org/10.5815/ijmecs.2016.02.08
DOI: https://doi.org/10.5815/ijmecs.2016.02.08
Google Scholar
Broucke, S., & Baesens, B. (2018). Practical Web Scraping for Data Science: Best practices and Examples with Python. New York: Apress. https://doi.org/10.1007/978-1-4842-3582-9
DOI: https://doi.org/10.1007/978-1-4842-3582-9
Google Scholar
Gil-Gaytán, O. L., & Núñez-Partido, A. (2017). Rasgos de personalidad de exportadores mexicanos con éxito. Revista Academia & Negocios, 3(1), 23–34.
Google Scholar
Koutra, G., Barbounaki, S., Kardaras, D., & Stalidis, G. (2017). A multicriteria model for Personnel selection in Maritime Industry in Greece. In 2017 IEEE 19th Conference on Business Informatics (CBI) (pp. 287–294). Thessaloniki. https://doi.org/10.1109/CBI.2017.52
DOI: https://doi.org/10.1109/CBI.2017.52
Google Scholar
Mamdani, E. H., & Assilan, S. (1975). An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller. International Journal of Man-Machine Studies, 7(1), 1–13. https://doi.org/10.1016/S0020-7373(75)80002-2
DOI: https://doi.org/10.1016/S0020-7373(75)80002-2
Google Scholar
Rianto, Budiyanto, D., Setyohadi, & Suyoto. (2017). AHP-TOPSIS on Selection of New University Students and the Prediction of Future Employment. In 2017 1st International Conference on Informatics and Computational Sciences (ICICoS) (pp. 125–130). Semarang. https://doi.org/10.1109/ICICOS.2017.8276349
DOI: https://doi.org/10.1109/ICICOS.2017.8276349
Google Scholar
Saaty, T. L. (1980). The Analytic Hierarchy Process. New York: McGraw-Hill.
DOI: https://doi.org/10.21236/ADA214804
Google Scholar
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
DOI: https://doi.org/10.1016/S0019-9958(65)90241-X
Google Scholar
Authors
Isaac FLORES-HERNÁNDEZisaac_camus@hotmail.com
Instituto Tecnológico de Apizaco, Computer Systems Department, Fco I Madero, Barrio de San José, 90300 Apizaco, Tlaxcala Mexico
Authors
Edmundo BONILLA-HUERTAInstituto Tecnológico de Apizaco, Computer Systems Department, Fco I Madero, Barrio de San José, 90300 Apizaco, Tlaxcala Mexico
Authors
Perfecto MALAQUIAS QUINTERO-FLORES* Instituto Tecnológico de Apizaco, Computer Systems Department, Fco I Madero, Barrio de San José, 90300 Apizaco, Tlaxcala Mexico
Authors
Oscar Atriano PONCESmartsoft America BA, Calle Adolfo López Mateos, Texcacoac, 90806 Chiautempan Mexico
Authors
José Crispín HERNÁNDEZ-HERNÁNDEZInstituto Tecnológico de Apizaco, Computer Systems Department, Fco I Madero, Barrio de San José, 90300 Apizaco, Tlaxcala Mexico
Statistics
Abstract views: 115PDF downloads: 34
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.
Similar Articles
- Yuriy TRYUS, Nataliya ANTIPOVA, Kateryna ZHURAVEL, Grygoriy ZASPA, INFORMATION TECHNOLOGY OF STOCK INDEXES FORECASTING ON THE BASE OF FUZZY NEURAL NETWORKS , Applied Computer Science: Vol. 13 No. 1 (2017)
- Fernando Andrés CEVALLOS SALAS, DIGITAL NEWS CLASSIFICATION AND PUNCTUACTION USING MACHINE LEARNING AND TEXT MINING TECHNIQUES , Applied Computer Science: Vol. 20 No. 2 (2024)
- Marcin BADUROWICZ, DETECTION OF SOURCE CODE IN INTERNET TEXTS USING AUTOMATICALLY GENERATED MACHINE LEARNING MODELS , Applied Computer Science: Vol. 18 No. 1 (2022)
- Jack OLESEN, Carl-Emil Houmøller PEDERSEN, Markus Germann KNUDSEN, Sandra TOFT, Vladimir NEDBAILO, Johan PRISAK, Izabela Ewa NIELSEN, Subrata SAHA, JOINT EFFECT OF FORECASTING AND LOT-SIZING METHOD ON COST MINIMIZATION OBJECTIVE OF A MANUFACTURER: A CASE STUDY , Applied Computer Science: Vol. 16 No. 4 (2020)
- Pornsiri KHUMLA, Kamthorn SARAWAN, IMPROVING MATERIAL REQUIREMENTS PLANNING THROUGH WEB-BASED: A CASE STUDY THAILAND SMEs , Applied Computer Science: Vol. 19 No. 4 (2023)
- Firas ALMUKHTAR, Nawzad MAHMOODD, Shahab KAREEM, SEARCH ENGINE OPTIMIZATION: A REVIEW , Applied Computer Science: Vol. 17 No. 1 (2021)
- Jarosław WIKAREK, Paweł SITEK, Mieczysław JAGODZIŃSKI, A DECLARATIVE APPROACH TO SHOP ORDERS OPTIMIZATION , Applied Computer Science: Vol. 15 No. 4 (2019)
- Grzegorz KŁOSOWSKI, Tomasz KLEPKA, Agnieszka NOWACKA, NEURAL CONTROLLER FOR THE SELECTION OF RECYCLED COMPONENTS IN POLYMER-GYPSY MORTARS , Applied Computer Science: Vol. 14 No. 2 (2018)
- Rowell HERNANDEZ, Robert ATIENZA, CAREER TRACK PREDICTION USING DEEP LEARNING MODEL BASED ON DISCRETE SERIES OF QUANTITATIVE CLASSIFICATION , Applied Computer Science: Vol. 17 No. 4 (2021)
- Maria CORDENTE-RODRIGUEZ, Simone SPLENDIANI, Patrizia SILVESTRELLI, MEASURING PROPENSITY OF ONLINE PURCHASE BY USING THE TAM MODEL: EVIDENCE FROM ITALIAN UNIVERSITY STUDENTS , Applied Computer Science: Vol. 16 No. 2 (2020)
You may also start an advanced similarity search for this article.