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<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "https://jats.nlm.nih.gov/publishing/1.3/JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xml:lang="ru">
  <front>
    <journal-meta>
      <journal-title-group>
        <journal-title>Computing, Telecommunication and Control</journal-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Информатика, телекоммуникации и управление</trans-title>
        </trans-title-group>
      </journal-title-group>
      <issn pub-type="epub">2687-0517</issn>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">11</article-id>
      <title-group>
        <article-title>Modern methods of automatic text summarization</article-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Современные методы автоматического реферирования</trans-title>
        </trans-title-group>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Tarasov</surname>
            <given-names>Sergey</given-names>
          </name>
          <email>Tarasov_sd@mail.ru</email>
        </contrib>
      </contrib-group>
      <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2010-12-10">
        <day>10</day>
        <month>12</month>
        <year>2010</year>
      </pub-date>
      <issue>6</issue>
      <issue-id pub-id-type="publisher-id">113</issue-id>
      <fpage>59</fpage>
      <lpage>74</lpage>
      <abstract xml:lang="en">
        <p>An in-depth analysis of existing approaches to the problem of automaticautomatic summarization of text is described. Discussed in detail various methods of monographs and summary (review) abstracting, shows the historical development of this area of research in the context of natural language processing by computers are considered. Ma Made a detailed classification of existing approaches, formulated their main advantages and disadvantages is described. We analyzed, compared and identified the most important and promising areas of modern research in the field of automatic summarization. Conclusions about the current state of research in this area are drawn.</p>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>text summarization</kwd>
        <kwd>multidocument summarization</kwd>
        <kwd>automatic creation of abstracts</kwd>
        <kwd>summary</kwd>
        <kwd>methods of text summarization</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
