The Collection and Processing Specifics of Online Data on Job Vacancies in the Russian Labor Market

Abstract

In the paper, the importance of online labor market data analyzing is considered, and the problems that arise during online data on job vacancies collection and processing are analyzed. The methodological approaches used by scientists for data mining of the labor market are reviewed. The data on job vacancies should be classified as semistructured data. In this regard, the analysis of data on job vacancies requires the use of data preparation procedures and algorithmic methods to extract the relevant information. If the data are used from different online job database, then it is necessary to form a common system of industries and professional areas. It is necessary to choose the profession title and the list of key competencies that define it, as well as identify synonyms among the competencies names. It is necessary to resolve the issue of wages level measuring, and to determine the strategy for processing job vacancy data instances in which some fields were not filled. The paper proposes an approach to build the core of professional competencies model based on the methods of the labor market data mining. The research object is the vacancies from the online labor exchange source HeadHunter. The results of extracting key professional competencies for IT specialists and sales managers are given in the paper. According to the study results, it was determined that further development of the methodology for the semi-structured data mining on the labor market is required.