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 <front>
  <journal-meta>
   <journal-id journal-id-type="publisher-id">Bulletin of Kemerovo State University. Series: Humanities and Social Sciences</journal-id>
   <journal-title-group>
    <journal-title xml:lang="en">Bulletin of Kemerovo State University. Series: Humanities and Social Sciences</journal-title>
    <trans-title-group xml:lang="ru">
     <trans-title>Вестник Кемеровского государственного университета. Серия: Гуманитарные и общественные науки</trans-title>
    </trans-title-group>
   </journal-title-group>
   <issn publication-format="print">2542-1840</issn>
   <issn publication-format="online">2541-9145</issn>
  </journal-meta>
  <article-meta>
   <article-id pub-id-type="publisher-id">70424</article-id>
   <article-id pub-id-type="doi">10.21603/2542-1840-2023-7-3-267-280</article-id>
   <article-id pub-id-type="edn">FEIQKS</article-id>
   <article-categories>
    <subj-group subj-group-type="toc-heading" xml:lang="ru">
     <subject>Междисциплинарные исследования языка</subject>
    </subj-group>
    <subj-group subj-group-type="toc-heading" xml:lang="en">
     <subject>Interdisciplinary Language Studies</subject>
    </subj-group>
    <subj-group>
     <subject>Междисциплинарные исследования языка</subject>
    </subj-group>
   </article-categories>
   <title-group>
    <article-title xml:lang="en">Artificial Intelligence in Interdisciplinary Linguistics</article-title>
    <trans-title-group xml:lang="ru">
     <trans-title>Искусственный интеллект в контексте  междисциплинарных исследований языка</trans-title>
    </trans-title-group>
   </title-group>
   <contrib-group content-type="authors">
    <contrib contrib-type="author">
     <contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-8667-6743</contrib-id>
     <name-alternatives>
      <name xml:lang="ru">
       <surname>Сорокина</surname>
       <given-names>Светлана Геннадьевна</given-names>
      </name>
      <name xml:lang="en">
       <surname>Sorokina</surname>
       <given-names>Svetlana Gennad'evna</given-names>
      </name>
     </name-alternatives>
     <email>lana40ina@mail.ru</email>
     <xref ref-type="aff" rid="aff-1"/>
    </contrib>
   </contrib-group>
   <aff-alternatives id="aff-1">
    <aff>
     <institution xml:lang="ru">Московский городской педагогический университет</institution>
     <city>Москва</city>
     <country>Россия</country>
    </aff>
    <aff>
     <institution xml:lang="en">Moscow City University</institution>
     <city>Moscow</city>
     <country>Russian Federation</country>
    </aff>
   </aff-alternatives>
   <pub-date publication-format="print" date-type="pub" iso-8601-date="2023-10-02T00:00:00+03:00">
    <day>02</day>
    <month>10</month>
    <year>2023</year>
   </pub-date>
   <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2023-10-02T00:00:00+03:00">
    <day>02</day>
    <month>10</month>
    <year>2023</year>
   </pub-date>
   <volume>7</volume>
   <issue>3</issue>
   <fpage>267</fpage>
   <lpage>280</lpage>
   <history>
    <date date-type="received" iso-8601-date="2023-07-21T00:00:00+03:00">
     <day>21</day>
     <month>07</month>
     <year>2023</year>
    </date>
    <date date-type="accepted" iso-8601-date="2023-08-14T00:00:00+03:00">
     <day>14</day>
     <month>08</month>
     <year>2023</year>
    </date>
   </history>
   <self-uri xlink:href="https://jstrategizing.kemsu.ru/en/nauka/article/70424/view">https://jstrategizing.kemsu.ru/en/nauka/article/70424/view</self-uri>
   <abstract xml:lang="ru">
    <p>Искусственный интеллект становится неотъемлемой частью различных наук, промышленных отраслей и повседневной жизни общества. Поскольку исследование искусственного интеллекта развивается в различных научных дисциплинах, его изучение требует комплексного, конвергентного подхода. Автор предлагает обзор существующих подходов к определению и интерпретации понятия искусственный интеллект с целью выявления его инвариантных характеристик, обуславливающих междисциплинарный характер искусственного интеллекта. Систематизируются ключевые драйверы и технологии развития искусственного интеллекта, основные модели его исследования; акцентируется уникальная способность искусственного интеллекта использовать знания, приобретать дополнительные знания и, анализируя и изучая способы их выражения и методы познания, достигать эффекта имитации интеллектуальной деятельности человека. Анализ определений исследуемого понятия позволяет сделать вывод о том, что важными тенденциями развития искусственного интеллекта являются его эмулятивное поведение, а также способность к постоянному развитию и изменениям, которые, с одной стороны, открывают новые исследовательские перспективы, а с другой – создают определенные трудности в понимании этих процессов. Среди технологий обучения искусственного интеллекта, играющих важную роль в его развитии, выделены алгоритмы, обработка больших данных и обработка естественного языка. Обзор существующих лингвистических исследований позволяет объединить исследовательские подходы в этой области вокруг основных задач интеллектуального анализа текстовых данных, среди которых основными являются поиск информации, извлечение знаний, классификация, аннотирование. Изучение и развитие искусственного интеллекта имеет важное значение для понимания его когнитивного потенциала и применения в различных сферах науки, промышленности и повседневной жизни.</p>
   </abstract>
   <trans-abstract xml:lang="en">
    <p>Artificial intelligence (AI) is becoming an integral part of various scientific disciplines, industries, and everyday life. AI studies cover quite a number of scientific fields, and the topic needs an integrated and convergent approach to address its multifaceted challenges. This paper provides an extensive survey of existing approaches to define and interpret the AI concept. The research objective was to identify the invariant characteristics of AI that underscore its interdisciplinary nature. The article categorizes the primary drivers, technologies, and key research models that fuel the advancement of AI, which possesses a unique capability to leverage knowledge, acquire additional insights, and attain human-like intellectual performance by analyzing expressions and methods of human cognition. The emulation of human intellectual activity and inherent propensity for continual evolution and adaptability both unlock novel research prospects and complicate the understanding of these processes. Algorithms, big data processing, and natural language processing are crucial for advancing the AI learning technologies. A comprehensive analysis of the existing linguistic research revealed an opportunity to unify various research approaches within this realm, focusing on pivotal tasks, e.g., text data mining, information retrieval, knowledge extraction, classification, abstracting, etc. AI studies make it possible to comprehend its cognitive potential applications across diverse domains of science, industry, and daily life.</p>
   </trans-abstract>
   <kwd-group xml:lang="ru">
    <kwd>искусственный интеллект</kwd>
    <kwd>когнитивная наука</kwd>
    <kwd>междисциплинарные исследования языка</kwd>
    <kwd>конвергентный подход</kwd>
    <kwd>управление искусственным интеллектом</kwd>
    <kwd>искусственная социальность</kwd>
    <kwd>интеллектуальный анализ</kwd>
   </kwd-group>
   <kwd-group xml:lang="en">
    <kwd>artificial intelligence</kwd>
    <kwd>cognitive science</kwd>
    <kwd>interdisciplinary language research</kwd>
    <kwd>convergent approach</kwd>
    <kwd>artificial intelligence control</kwd>
    <kwd>artificial sociality</kwd>
    <kwd>intellectual analysis</kwd>
   </kwd-group>
  </article-meta>
 </front>
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