АНАЛИЗ ТРЕБОВАНИЙ И РАЗРАБОТКА АЛГОРИТМОВ ИНТЕЛЛЕКТУАЛЬНЫХ СЕРВИСОВ МОНИТОРИНГА

Abstract

The paper considers the problems of strategic analysis and the choice of directions for the developmentof innovative enterprises in the conditions of transition to the 6th technological order and industry4.0. The main levels of analysis are determined. The objectives of the strategic analysis are outlinedbased on the scale of the research being conducted. The analysis tasks are highlighted, the solution ofwhich will allow achieving the set goals. The complexity of solving global monitoring tasks, which arecaused by a large volume of heterogeneous and unstructured information, is shown. In these conditions,thematic search and analytical processing of information cannot be performed without the use of automated information and analytical systems and the creation of search services based on artificial intelligence.A general monitoring procedure is proposed. The main stages of monitoring technological trendsare defined, the tasks to be solved within a specific stage and the planned result are shown. Based on thegeneral monitoring procedure, the main priority functions that the developed services should have aredetermined. As well as the problems of their development and structuring of the received information inthe form of information objects and clustering of documents. In contrast to the well-known global monitoringsystems, in which the search is based on indicators: an increase in the use of keywords, an increasein the number of new authors, quoting works from related fields. Algorithms are proposed thatprovide the definition of reference topics, assessment of ranking and relevance of information. The descriptionof the algorithms is given on the example of creating a summary information table, with thehelp of which the interrelationships of documents of scientific and technological development in eachdirection of monitoring and the search for specific documents in the database are formed. The constructionof search services based on the presented algorithms will ensure the allocation of reference topicsof documents, provide more reliable results of clustering of unstructured information and the formationof scientific and technological trends in information and analytical complexes. To implement the algorithm,it is proposed to use the Python programming language. The implementation of these algorithmswill improve the quality and efficiency of information retrieval in conditions of a large volume of unstructuredinformation.