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In modern conditions of rapid growth of textual information volumes, efficient extraction of named entities becomes a key aspect of data analysis in various fields of science and technology.
The task of text data analysis is extremely relevant for a number of internal services of the Joint Institute for Nuclear Research (JINR), in particular, in the context of development of the JINRex excursion planning and accounting system, which determines the necessity to choose the most efficient methods of information processing.
The comparison of methods of extraction of named entities in the algorithm of processing text data on excursions is carried out. The results of the algorithm allow to obtain statistical information about the conducted events from natural language texts containing a brief description about the name of the excursion and the target audience.
This paper presents a practical comparative analysis of different approaches to the extraction of named entities, with a focus on their applicability in solving the tasks of text analysis and processing within the framework of support and development of JINR internal services.
