The process of selecting a profession in accordance with the needs of the individual and the requirements of the city's labor market is a complex, multi-step, iterative process that requires consideration of a large number of parameters and prerequisites. The determination of professional inclinations is based on the analysis of the accumulated results of vocational guidance tests that help to identify human abilities in a certain field of activity and allow you to choose a branch of professional activity. Labor market monitoring is in order to identify trends in factors affecting the supply and demand of work in the city. Determining the development prospects requires a convenient tool for assessing trends in the volatility of the demand for the regional labor market, which is carried out in several stages, consisting of the processes of collecting, verifying and accumulating statistical information by the key coordinates of the phase space; forming a group of basic methods for predicting the lower level, suitable for working with time series, taking into account their features (stationary, omission, noises, etc.); development of an adequate model of adaptive integration of forecast estimates from different sources; support of the interactive mode of parametric adjustment both for the forecasting models of the lower level and the model of complexation.
The level of development of modern information technologies and communication
systems [
Analysis of the Research State
Formalization of the functioning conditions of a complex social and economic object,
particularly quantitative indicators of its external and internal environment [
This approach contributes to the formation of predictive estimates of coordinate
values, phase space for effective strategic analysis [
An example of such complex objects is an educational social and communication environment of a large city that is a multidimensional and polyfunctional complex system that functions and develops in real time in a defined territorial space (real or virtual one) whose activities are managed and coordinated as well as pedagogical influence of objective and subjective factors on subjects of educational process is implemented.
Several researchers suggest using information technologies and information systems to help automate the process of choosing a profession by smart city residents. There is practically no opportunity in one information point to analyze information about a person as an object of vocational guidance and educational work and to obtain comprehensive information and analytical data of the regional labor market and educational services. Information is mainly provided without proper authenticity and structuring.
Certain technological developments are in the context of choosing a particular specialty while entering a higher education institution. In a number of papers, it is suggested to use the modular principle when developing a recommender system that facilitates the implementation process of choosing a specialty in a particular institution. 2
The information sources about the professional orientation of the World Wide Web are divided into integrated and independent web pages.
Integrated web pages are the pages of professional counseling organizations and institutions. They contain both general and specific information for this institution. As a rule, their use is free of charge.
Independent web pages are non-interlinked pages that include information about vacancies, professions, educational positions of schools and higher education institutions, work offers with the description of an enterprise, as well as they also provide assistance with decision-making on choosing a future profession or changing it.
According to the functional purpose, information technologies focused on
providing solutions to the problems of professional orientation of young people, can be
conditionally divided into the following classes [
Sites of educational institutions that inform about the admission conditions and training directions, are aimed at encouraging graduates to enter this or that higher educational institution. Such resources are not oriented to maintain the processes of an individual profession choice, do not give substantiated advice to an entrant, but, instead, create uncertainty about the profession, as a young person is hesitant about several equal or similar options for choosing a possible specialty.
Educational portals. This type includes resources that contain comprehensive information about all aspects that relate to education in general. However, such sites do not contain clear advice for people who choose a profession, do not provide objective testing for the subject of professional orientation, which would help to consider the individual abilities choosing a specialty, an inclination for a certain activity type, psychophysical abilities of a young person, regional aspects, etc.
Employment resources. This type of Internet resources is the most popular among similar tools. As a rule, they can help you to get information about the list of vacancies, their features and additional requirements, the availability of vacancies in different regions, as well as to contact an employer. The disadvantage of such IT is the lack of information on educational institutions, where it is possible to obtain the relevant profession, requalify or get the second higher education.
Test resources. This type of IT offers a good selection of different psychological tests that relate to the choice of profession. As a rule, their main disadvantage is that they do not contain information on the further orientation of a profession searcher, especially about educational institutions, aspects of the profession, prospects for employment, the need for a profession in our time, and so on.
The comparison results of the functional characteristics of the existing legal and national online resources of professional orientation are shown in Table 1 ("+" indicates the functions implemented by the system, "-" – not implemented, "+ /" – implemented partly). The analysis was conducted using the following parameters: P1 is to definite professional inclinations and abilities of a person; P2 is to inform the searcher about profession and its characteristics; P3 is to inform about the educational service market; P4 is the labor market monitoring;
P5 is to provide personalized recommendations on the profession choice according to personal inclinations and labor market needs;
P6 is the formation of an individual learning trajectory. Internet project + + + - - “Proforientation” The analysis showed that well-known information technologies and Internet resources are specialized and focused on solving only a part of the problems that arise in the process of choosing a professional orientation.
Considering the fact that the risk measure in case of wrong planning is sufficiently
significant, the information and technological support for training specialists seems to
be an urgent task, i.e. the system creation of interconnected information technologies
designed to reduce labor-capacity and improve the task quality for the organization of
specialist training. Obviously, the prognostic support of such systems should be based
on the methodology of scientific forecast, while at the same time characterized by a
possibility of interactive adjustment and adaptation [
The relevance of predictive support can be argued by the fact that the Nobel Prize in 2013 was received by American economists on the basis of research in the prognostic field.
In the paper [
An adequate amount of data obtained during the research provides a high accuracy
of forecasting, creation of effective methods and models [
Prognostic support is one of the key elements of predictive analytics systems. Its
results are the information basis for users, and, consequently, should be characterized
by accuracy, reliability, stability [
The option of providing a full spectrum of methods and means of prognosis in solving management tasks through the synthesis of specialized forecasting information complexes considering the available means of Data Mining is promising under existing conditions.
It means the development of a forecasting support model, as well as the
construction of a trajectory of forecasting research, namely the development or selection of
methods for setting up the lower-level models and the synthesis of an adaptive model
for the compilation of predictive estimates at the upper level [
Specialized forecasting centers, having a modern methodological base and access
to the sector monitoring bases, are forced to solve periodically the problem of
choosing forecasting model and consolidating forecasts [
However, it should be considered that forecasts are useful for planning only if the
forecasting components are well thought out and the limitations contained in the
forecast are frankly named. It is required [
- to determine the required accuracy of the forecast, based on what decisions are to be taken on its basis;
- to identify the changes that must take place so that the forecast turns out to be truthful; to assess the probability of the relevant event occurrence; - to determine the forecast components and take care of data sources; - to determine how valuable the experience preparing the forecast is, whether there are grounds for drawing up a forecast based on this experience, how simple or inexpensive it will be to obtain reliable information about the experience of the past; - to distinguish how structured the forecast should be.
Thus, the overall logical sequence of forecasting development is reduced to the following main stages (Fig. 1): Stage 1 is the development of the research program (the goals and tasks of forecasting are formulated; the task for forecasting, nature, scale, object, warning period and forecast horizon are specified; the methods, structure and organization of the research are determined).
Stage 2 is collecting the necessary information for forecasting; reliable statistical information about the studied system is required for the development of a forecasting model;
Stage 3 is the selection of statistical data, their consolidation, verification of probability for ensuring accuracy of forecasting, system analysis and generalization;
Stage 4 is numerical simulation based on the collected statistical information (the prototype creation of a predictive model that most closely matches the characteristics of the collected data and can provide a minimum prognostic error, model evaluation and diagnostic testing);
Stage 5 is an extrapolation of the selected model (involves the actual reception of the required forecast);
Stage 6 is an estimation of reliability and accuracy, as well as validity (verification) of the forecast. The estimation of the received forecast consists in comparison of the calculated values with the values that can be observed. For this purpose, a part of the most recent actual information is usually excluded from the data set that is being analyzed, and prediction is used for recent past periods for which the studied values are already known. If the results coincide, there are reasons to be more confident that the probability level of the forecast is high, if not it is necessary to search and eliminate the problems or drawbacks in the methodology for developing the forecast;
Stage 7 is the development of recommendations for decision-making in the field of management.
Regardless of the forecast type, the main task of forecasting is to show the links between the past and the future, between the information about the process in the controlled time period and the nature of process further, and the most accurate description of these relationships. The fulfillment of this task ensures achievement of the main goal of forecasting, namely the reduction of the uncertainty level in which the leader must make decisions, obtain scientifically substantiated variants of development trends or change in the indicators of the controlled object state in time and space, drawing up a sufficiently accurate, practical, balanced and useful prognosis that can be effectively used in management, and its benefit will exceed the cost of its development. 4
2) make of a group of basic methods of forecasting the lower level, suitable for working with time series, taking into account their features (stationary, omissions, noise, etc.);
3) making of an adequate model of adaptive integration of forecast estimates of the labor market of the IT industry;
4) support of interactive mode of parametric adjustment, both predictive models of the lower level and integration model, which allows a reasonable intervention of the subject of management.
It is proposed to provide multi-layer prognostic support, which is consisted of
several levels [
At the first level, there are statistical forecasting models. Information technology
forms a proven set of predictive models and methods specific to its prognostic
activity. For example, studying the dynamic processes along with traditional methods, the
new methods are more and more applicable and, in particular, a popular method of
analysis and forecasting of time series called caterpillar SSA [
The SSA method has a very wide scope of application, is relatively simple to manage, it is natural, powerful, distinguished by the visibility, but it remains lowincome in applications.
At the second level, there are models that are called selective predictive models, aggregated on the basis of solution rules.
At the next level, there are combined forecasting models [30] that involve structural and parametric exchanges in order to parry the natural disadvantages of the base models.
At the fourth logical level of the model, there are models of forecasting estimation and the consolidated forecasts can be synthesized using multiple sources.
The research confirms that forecasting, regardless of the used concrete tools of forecasting at the lower level, is provided by top-level models (complex forecasting estimation) that can guarantee satisfactory quality of forecasting support, namely, the accuracy of adaptive predictive support of the regional labor market model of the IT industry.
Thus, by developing the information technology of estimating vacancies on the labor market, it is suggested to use prognostic technology, which allows predicting the development of the labor market in a particular industry. The research is conducted using data from the IT industry and further research provides the creation of a comprehensive model of this industry and development prospects. 29. Stepanov, D. V., Golyandina, N.E.: SSA-based approaches to analysis and forecast of multidimensional time series. Proc. of the 5th St. Petersburg Workshop on Simulation, St.Petersburg, 293–298 (2005). 30. Kut, V., Kunanets, N., Pasichnik, V., Tomashevskyi, V.: The procedures for the selection of knowledge representation methods in the “virtual university” distance learning system. Advances in Intelligent Systems and Computing, Volume 754, 713-72 (2019)