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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="en">
  <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">12</article-id>
      <article-id pub-id-type="doi">10.18721/JCSTCS.11412</article-id>
      <title-group>
        <article-title>Process extraction from educational texts</article-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Извлечение моделей бизнес-процессов из обучающих материалов</trans-title>
        </trans-title-group>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Timofeev</surname>
            <given-names>Dmitry</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
          <email>dtim@dcn.icc.spbstu.ru</email>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Samochadin</surname>
            <given-names>Aleksandr</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
          <email>Samochadin@soft-consult.ru</email>
        </contrib>
      </contrib-group>
      <aff id="aff1">Peter the Great St.Petersburg Polytechnic University</aff>
      <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2018-12-28">
        <day>28</day>
        <month>12</month>
        <year>2018</year>
      </pub-date>
      <volume>11</volume>
      <issue>4</issue>
      <fpage>162</fpage>
      <lpage>170</lpage>
      <abstract xml:lang="en">
        <p>Business process modeling plays an important role in analysis and optimization of organizational processes. Automation of process models is particularly crucial in domains where processes involve mostly intellectual activity that is not properly documented. Software development is an example of a domain with these properties. Educational materials like instructions and guides, blog posts, or conference talks are an important source of information about the processes in this case. Known algorithms of process extraction pose strict requirements to the input text. In this paper, we propose an approach to process extraction from complex sources containing descriptions of multiple processes and text blocks unrelated to the process model. In order to account for these aspects, the method considers not only standard lexical and syntactic properties of the text but also its structure and markup.</p>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>business process</kwd>
        <kwd>process modeling</kwd>
        <kwd>process extraction</kwd>
        <kwd>natural language processing</kwd>
        <kwd>text analysis</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
