@ARTICLE{26583204_375001355_2020, 
	author = {Andrei Ternikov and Ekaterina Aleksandrova}, 
	keywords = {, job vacancies in IT sector, online vacancies, unstructured data analysis, labor market, demand on skills of job candidatescombinations of skillsets},
	title = {<p class="text">Demand for skills on the labor market in the IT sector</p>},
	journal = {},
	year = {2020},
	number = {2 Vol.14},
	pages = {64-83},
	url = {https://bijournal.hse.ru/en/2020--2 Vol.14/375001355.html},
	publisher = {},
	abstract = {&nbsp; &nbsp; &nbsp; One of the most dynamically changing parts of the labor market relates to information technologies. Skillsets demanded by employers in this sphere vary across different industries, organizations and even certain vacancies. The educational system in the most cases lags behind such changes, so that obsolete skillsets are being taught. This article proposes an algorithm of skillsets identification that allows us to extract skills that are needed by companies from different occupational groups in the information technologies sector. Using the unstructured online-vacancies database for the Russian regional labor market, skills are extracted and unified with the use of TF-IDF and n-grams approaches. As a result, key specific skillsets for various occupations are found. The proposed algorithm allows us to identify and standardize key skills which might be applicable to create a system of Russian classification for occupations and skills. In addition, the algorithm allows us to provide lists of the key combinations of skills that are in high demand among companies inside each particular occupation.},
	annote = {&nbsp; &nbsp; &nbsp; One of the most dynamically changing parts of the labor market relates to information technologies. Skillsets demanded by employers in this sphere vary across different industries, organizations and even certain vacancies. The educational system in the most cases lags behind such changes, so that obsolete skillsets are being taught. This article proposes an algorithm of skillsets identification that allows us to extract skills that are needed by companies from different occupational groups in the information technologies sector. Using the unstructured online-vacancies database for the Russian regional labor market, skills are extracted and unified with the use of TF-IDF and n-grams approaches. As a result, key specific skillsets for various occupations are found. The proposed algorithm allows us to identify and standardize key skills which might be applicable to create a system of Russian classification for occupations and skills. In addition, the algorithm allows us to provide lists of the key combinations of skills that are in high demand among companies inside each particular occupation.}
}