New tasks of human resource management require the analysis of huge volumes of semi-structured text information. Methods of text processing and machine learning can significantly improve its effectiveness in case they take into consideration the features of tasks to be solved. The article describes actual analytical problems of human resource management, characteristics of information support of these problems, shortcomings and assumptions of frequently used methods of both classes in the tasks context. An example of applying test processing and machine learning methods in the task of compliance assessment is given in the article as well.
|Translated title of the contribution||Text processing and machine learning methods in HRM applications: opportunities and features|
|Publication status||Published - 30 Oct 2018|