A cognitive algorithm and a text annotation program

Purpose of research. The research is aimed at exploring the possibilities of using cognitive technologies (CT) to effectively solve poorly formalized tasks in the field of analyzing large amounts of textual data. Special attention is paid to the task of automatic text annotation, which is one of the most important problems of modern science and technology, stimulating the active development of artificial intelligence and machine learning methods.

Methods. To achieve this goal, an extractive method of automatic summary compilation was used. This approach involves selecting the most significant fragments of the source text by highlighting individual sentences or phrases based on certain criteria. The following selection criteria were used: frequency of occurrence of words; semantic importance of words and expressions; position of sentences within the document. These indicators allow you to highlight the main thoughts of the text and create a compact summary that preserves the meaning of the source material.

Results. During the experiments, a program was developed in the Python programming language that implements the extracted method of taking notes. The algorithm is based on an analysis of the frequency of occurrence of keywords in the text, which ensures an effective assessment of the significance of each sentence. The program has a number of advantages: simplicity of implementation and operation; open source code, which makes it easy to adapt the solution to the specific needs of users; high efficiency in processing significant amounts of textual information. The developed tool demonstrates the ability to effectively create a summary of the text, while maintaining the basic meaning and structure of the original content.

Conclusion. The use of a cognitive algorithm has significantly improved the productivity of the text information analysis and processing process. The proposed methodology is capable of automating routine operations for making notes, helping specialists quickly get a general idea of the contents of large documents and publications. This is especially important in the context of the modern information society, characterized by ever-growing data flows that require rapid and high-quality comprehension. Thus, the study showed the prospects of introducing cognitive technologies into the field of automation of intellectual work and offered a practical solution to the urgent problem of taking notes on large amounts of information, which can become an important assistant for specialists and researchers.

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