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Industrial Data
versión impresa ISSN 1560-9146versión On-line ISSN 1810-9993
Resumen
MAMANI RODRIGUEZ, Zoraida. Machine Learning Process to Determine the Social Demand for IT Professional Jobs. Ind. data [online]. 2022, vol.25, n.2, pp.275-300. ISSN 1560-9146. http://dx.doi.org/10.15381/idata.v25i2.21643.
Machine learning is a branch of artificial intelligence that uses scientific computing, mathematics and statistics through automated techniques to solve problems based on classification, regression and clustering. Social demand refers to the need for service and product of the professional training process, expressed by interest groups, aimed at contributing to national development, as established by the quality assurance policy of university higher education and national licensing and accreditation models. In this context, this paper conducts research based on job positions of IT professionals posted n web portals, designs a machine learning process with an unsupervised approach, extracts occupational profiles, designs a multidimensional model, applies k-means clustering when determining clusters of job positions by similarity, and reports the results obtained.
Palabras clave : machine learning process; clustering; k-means; social demand; IT professionals.