PNIPU: Denograph. Intelligent denotative analytics system for IT personnel preparation management

Main article: Data mining Data mining

2022: Software Presentation

A young scientist from Perm Polytechnic has created software to optimize the training of IT specialists. The University announced this on December 28, 2022.

The development of the digital economy is one of the priorities of the state policy of the Russian Federation. In addition to automating production and investing in technology, it includes the training of highly qualified IT specialists. The computer program developed in the Perm Polytechnic University "Denograf will help to train the IT specialists answering to real inquiries of labor market. Intelligent denotative analytics system to manage IT personnel training. "

This program collects data on employers' requirements for an applicant from aggregator sites, analyzes them and, using a mathematical model-description of a specialist, forms recommendations for training courses. They include the required competencies and the number of hours required to obtain them. The system allows you to improve not only university disciplines, but also programs of additional professional education.

At the same time, concepts are not taken out of context, on the contrary, the program indicates thematic connections within the subject area. This is possible by using a denotative approach to text analysis.

Denotat is a word or phrase in a natural language text that relates to an object or phenomenon of a subject area and expresses that meaning in said text. In IT search job texts, these are the key concepts used to describe IT competencies. Such denotates include, for example, designations of programming languages, technologies, tools, concepts, etc. Then a "semantic map" is built, which allows tracing the connection between concepts, "explained Denis Yarullin, program developer, senior lecturer at the Department of Information Technologies and Automated Systems.

To assess the effectiveness of the developed program, a small experiment was conducted with the participation of students who graduated from the 3rd year of the directions "Software Engineering" and "Informatics and Computer Engineering" of PNIPU and several potential employers. Company representatives conducted standardized interviews with each of the students and completed a questionnaire, assessing their competencies and the prospect of employment. The results of the primary interviews showed that although students have sufficient competencies in algorithmization and programming, the lack of competencies associated with the required technologies and understanding of their relationship greatly reduce the likelihood of recommending employment.

Then the students underwent short-term training under the intensive program, compiled taking into account the recommendations of the information system, and again met with employers. The results of repeated interviews showed an improvement in indicators for all criteria: the average overall level of training increased by 9%; ownership of the necessary technology stack for employers - by 60%; technical outlook - by 46%. As a result, the likelihood of further employment increased by 40%.