Abstract
The research work presented within this paper solves the problem of automated search for heterogeneous data in social media of the Internet (SMI). Building a system for obtaining and subsequent analysis of heterogeneous data in SMI – a complex multi-stage process in which specialists of various profiles and qualifications participate. Therefore, one of the main problems in the design of such systems is the coverage of all aspects of the functioning of the software-analytical complex, providing a common language for specialists, which allows us to uniquely, and clearly, understandably formulate the basic concepts of the projects. One of the main and basic tasks in analyzing the pages of a SMI user is to build algorithms for analyzing the user data environment (UDE). The quality of software will depend on the implemented algorithms. The construction of such algorithms, on the one hand, provides an understanding of the process of forming functional individual modules of the system and their interaction, on the other hand, laying a qualitative foundation in the future system. Algorithms for data analysis in the SMI will be designed based on the basic principles of behavior of the user registered in it.
Highlights
FORMATION OF A SET OF INPUT DATA FROM THE USERIt is necessary to obtain from the user a piece of information in which it will be indicated what exactly should be found and analysed [7]
Today, various techniques and approaches for the analysis of social media of the Internet (SMI) are presented
The SMI server checks the correctness of the input by sending a request to the target resource, if the answer is correct [11], this resource is added to the lists of available sources
Summary
It is necessary to obtain from the user a piece of information in which it will be indicated what exactly should be found and analysed [7]. The initial stage of the algorithm will be the stage of generating input data for the search. Input data contains two types of signs: main and auxiliary. The main signs are signs by which the user can be found. Auxiliary signs are signs that are not used on their own, but supplement the main. The input data set will be formed in accordance with the constructed article [8]. The user can enter additional parameters manually, while specifying the parameters that must be used to search for these signs. If in the future the parameter is successfully identified and found, it will be added to the input data set
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