In recent years, due to significant changes in the labor market, companies have become more likely to face various problems when searching and selecting candidates. The main reason for these problems is that the existing Internet resources for finding candidates do not allow you to find a specialist with the required set of competencies and fully evaluate his experience, skills, achievements and personal characteristics. As a result, it becomes necessary to create a service for finding exclusive specialists. Most of these specialists do not have a resume in the public domain, are not looking for a job, but are ready to consider interesting offers. As a result, this work is devoted to the study of the possibility of finding specialists with unique competencies on the Internet based on the analysis of their digital footprint. The hypothesis is that it is possible to get a complete profile of a unique specialist if you collect, combine and analyze data from various sources. In the course of this work, the possibilities provided by open data sources on the Internet were analyzed, as well as the scientometric indicators of a specialist and the parameters of his reliability were determined. An algorithm for searching for the required specialists based on these data has been compiled, an automated system implementing this search has been designed, developed and tested.

The task of reducing the time for the purchase of essential goods is especially relevant in cases of shortage of free time of buyers. To do this, it is necessary to predict and estimate the time required to purchase goods. Traditional approaches based on cartographic systems do not provide estimates and forecasts, but only allow you to build a route to the right place based on an assessment of the traffic situation. For this reason, the problem of developing a more modern model is relevant, taking into account such factors as the infrastructural location of the store, user evaluation, and the workload of the store. The paper proposes an information model that includes such time costs of the buyer as the search for goods, the route to the place of sale of goods, the purchase of goods. The time spent on the purchase of goods is described using elements of queuing theory. Statistical and direct methods for assessing the workload and queues in the store are highlighted. The developed generalized model contains the parameters necessary to estimate the required time using statistical methods which include traffic forecasting based on user ratings and reviews, analysis of the infrastructure location and public video surveillance cameras, public Application Programming Interface of stores, and Internet services. Correction coefficients have been introduced to adjust the estimation of model parameters depending on the infrastructure location of the store and user ratings. A new information model has been formulated that allows taking into account the dependence of the time required to purchase emergency goods on the workload of the store, its infrastructure location, ratings and user reviews. The simulation model is developed in the AnyLogic environment. An example of using the model to estimate the average time spent on the purchase of emergency goods is demonstrated. The simulation results are consistent with the conducted experiment in which purchases of emergency goods were made in various stores in Saint Petersburg. The developed model can be used when searching for the optimal route to the place of sale of essential goods when planning the construction of stores as well as in the areas of marketing and delivery of goods.

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