Abstract
The information technology (IT) sector has not only created the largest number of jobs but has also contributed to greater employability in other sectors. Thanks to major advances in computing, the analysis of large volumes of data for extraction of information unknown a priori, has become a trend in all sectors and its benefits and advantages are unquestionable. The aim of this research work is to extract knowledge from employability information for market trend analysis and use this knowledge to adapt the user’s search for work to their profile and guide them accordingly. To this end, existing employability and training information will be retrieved, analysed and a platform will be created to allow the user to easily visualise the results, enabling users with no knowledge of data analysis to perform studies based on machine learning.
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References
Marx, P.: The effect of job insecurity and employability on preferences for redistribution in Western Europe. J. Eur. Soc. Policy 24(4), 351–366 (2014)
Wheeler, A., Austin, S., Glass, J.: E-mentoring for employability. In: EE2012–Innovation, Practice and Research in Engineering Education, pp. 1–9 (2012)
Martínez, J.M., Vázquez-Ingelmo, A., García-Peñalvo, F.J., Michavila, F., Martín-González, M., Cruz-Benito, J.: Barómetro de empleabilidad y empleo universitarios. Edición Máster 2017. Observatorio de Empleabilidad y Empleo Universitarios (2018)
Chen, M., Mao, S., Liu, Y.: Big data: a survey. Mob. Netw. Appl. 19(2), 171–209 (2014)
Chamoso, P., Rivas, A., Rodríguez, S., Bajo, J.: Relationship recommender system in a business and employment-oriented social network. Inf. Sci. 433, 204–220 (2018)
Spink, A., Jansen, B.J.: A study of web search trends. Webology 1(2), 4 (2004)
Slamet, C., Andrian, R., Maylawati, D.S.A., Darmalaksana, W., Ramdhani, M.A.: Web scraping and Naïve Bayes classification for job search engine. In: IOP Conference Series: Materials Science and Engineering, vol. 288, no. 1, p. 012038. IOP Publishing, January 2018
García-Peñalvo, F.J., Cruz-Benito, J., Martín-González, M., Vázquez-Ingelmo, A., Sánchez-Prieto, J.C., Therón, R.: Proposing a machine learning approach to analyze and predict employment and its factors. Int. J. Interact. Multimedia Artif. Intell. 5(2), 39–45 (2018)
Schwaber, K.: Scrum development process. In: Sutherland, J., Casanave, C., Miller, J., Patel, P., Hollowell, G. (eds.) Business Object Design and Implementation, pp. 117–134. Springer, London (1997). https://doi.org/10.1007/978-1-4471-0947-1_11
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Chamoso, P., González-Briones, A., García-Peñalvo, F.J. (2019). Data Analysis Platform for the Optimization of Employability in Technological Profiles. In: De La Prieta, F., et al. Highlights of Practical Applications of Survivable Agents and Multi-Agent Systems. The PAAMS Collection. PAAMS 2019. Communications in Computer and Information Science, vol 1047. Springer, Cham. https://doi.org/10.1007/978-3-030-24299-2_29
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DOI: https://doi.org/10.1007/978-3-030-24299-2_29
Publisher Name: Springer, Cham
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