{'fraction_non_alphanumeric': 0.013422818791946308, 'fraction_numerical': 0.0, 'mean_word_length': 5.426724137931035, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Algorithm for Searching Experts in Scientometric Systems

The use of modern methods of thematic analysis for the analytical processing of large amounts of information is currently used in almost all spheres of human activity. Scientometrics is one such area. Research carried out in this area shows that the statistical characteristics of citation rates are highly dependent on the thematic area of papers at hand. In this regard, systems for calculating citation indicators and constructing assessments of the quality of scientific works, ranks of authors or organizations should take into account the thematic area of researchers in order to normalize scientometric indicators. Many scientometric systems and citation systems use subject headings for information retrieval and processing. The world famous citation systems, including WoS, Scopus, Google Shcolar, and others have such headings. Important practical tasks that can be solved using the methods of thematic classification are: assessment of the dynamics of the development of thematic areas in an organization, in a particular country and in world science as a whole; search for articles on a given topic; search and assessment of the authority of experts; search for journals for publication and other urgent tasks. The authors have created software implementations of algorithms for solving some of the listed problems, and research is being conducted to create new effective mathematical models and algorithms in this area.