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<article article-type="research-article" dtd-version="1.3" xml:lang="en">
  <front xmlns:xlink="http://www.w3.org/1999/xlink">
    <journal-meta>
      <journal-id journal-id-type="elibrary">https://www.elibrary.ru/title_about_new.asp?i</journal-id>
      <journal-title-group>
        <journal-title>Materials physics and mechanics</journal-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Механика и физика материалов</trans-title>
        </trans-title-group>
      </journal-title-group>
      <issn pub-type="epub">1605-8119</issn>
    </journal-meta>
    <article-meta xmlns:xlink="http://www.w3.org/1999/xlink">
      <article-id pub-id-type="publisher-id">8</article-id>
      <title-group>
        <article-title>Document Classification Using Weighted Ontology</article-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Document Classification Using Weighted Ontology</trans-title>
        </trans-title-group>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Bevainyte</surname>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Būtenas</surname>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
      </contrib-group>
      <aff id="aff1">Vilnius University</aff>
      <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2010-07-03">
        <day>03</day>
        <month>07</month>
        <year>2010</year>
      </pub-date>
      <volume>9</volume>
      <issue>3</issue>
      <fpage>246</fpage>
      <lpage>250</lpage>
      <self-uri xmlns:xlink="http://www.w3.org/1999/xlink" content-type="pdf" xlink:href="https://mpm.spbstu.ru/userfiles/files/MPM_9_3_P08.pdf"/>
      <abstract xml:lang="en">
        <p>This paper presents document comparison and classification model for Lithuanian language texts based on weighed ontology. The tests have been performed to measure several aspects: i) quality of comparison of documents; ii) optimal size of ontology; iii) type of part of speech words used to create ontology. Final results indicate 96% of correct classification cases and suggest that all the main part of speech terms should be used from the text. The proposed model can be used to classify texts more efficiently than keyword based systems.</p>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>Ontology</kwd>
        <kwd>Lithuanian language texts</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
