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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">109</journal-id>
      <journal-id journal-id-type="index">urn:lsid:arphahub.com:pub:3dc5f44e-8666-58db-bc76-a455210e8891</journal-id>
      <journal-title-group>
        <journal-title xml:lang="en">JUCS - Journal of Universal Computer Science</journal-title>
        <abbrev-journal-title xml:lang="en">jucs</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="ppub">0948-695X</issn>
      <issn pub-type="epub">0948-6968</issn>
      <publisher>
        <publisher-name>Journal of Universal Computer Science</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.3217/jucs-011-11-1820</article-id>
      <article-id pub-id-type="publisher-id">28506</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group subj-group-type="scientific_subject">
          <subject>H.3.0 - General</subject>
          <subject>H.3.3 - Information Search and Retrieval</subject>
          <subject>H.3.4 - Systems and Software</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Integrating Lite-Weight but Ubiquitous Data Mining into GUI Operating Systems</article-title>
      </title-group>
      <contrib-group content-type="authors">
        <contrib contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>Wei</surname>
            <given-names>Li</given-names>
          </name>
          <email xlink:type="simple">wli@cs.ucr.edu</email>
          <xref ref-type="aff" rid="A1">1</xref>
        </contrib>
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Keogh</surname>
            <given-names>Eamonn</given-names>
          </name>
          <xref ref-type="aff" rid="A1">1</xref>
        </contrib>
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Xi</surname>
            <given-names>Xiaopeng</given-names>
          </name>
          <xref ref-type="aff" rid="A1">1</xref>
        </contrib>
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Lonardi</surname>
            <given-names>Stefano</given-names>
          </name>
          <xref ref-type="aff" rid="A1">1</xref>
        </contrib>
      </contrib-group>
      <aff id="A1">
        <label>1</label>
        <addr-line content-type="verbatim">University of California, Riverside, United States of America</addr-line>
        <institution>University of California</institution>
        <addr-line content-type="city">Riverside</addr-line>
        <country>United States of America</country>
      </aff>
      <author-notes>
        <fn fn-type="corresp">
          <p>Corresponding author: Li Wei (<email xlink:type="simple">wli@cs.ucr.edu</email>).</p>
        </fn>
        <fn fn-type="edited-by">
          <p>Academic editor: </p>
        </fn>
      </author-notes>
      <pub-date pub-type="collection">
        <year>2005</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>28</day>
        <month>11</month>
        <year>2005</year>
      </pub-date>
      <volume>11</volume>
      <issue>11</issue>
      <fpage>1820</fpage>
      <lpage>1834</lpage>
      <uri content-type="arpha" xlink:href="http://openbiodiv.net/4C0C9BA6-DCAF-5830-AEFA-97A3393744FD">4C0C9BA6-DCAF-5830-AEFA-97A3393744FD</uri>
      <uri content-type="zenodo_dep_id" xlink:href="https://zenodo.org/record/6996891">6996891</uri>
      <permissions>
        <copyright-statement>Li Wei, Eamonn Keogh, Xiaopeng Xi, Stefano Lonardi</copyright-statement>
        <license license-type="creative-commons-attribution" xlink:href="" xlink:type="simple">
          <license-p>This article is freely available under the J.UCS Open Content License.</license-p>
        </license>
      </permissions>
      <abstract>
        <label>Abstract</label>
        <p>Most visualization tools introduced in the literature are specialized for a particular task. In this work, we introduce a novel framework which allows visualization to take place in the background of normal day to day operations of any GUI based operating system such as MS Windows, OS X or Linux. Our system works by replacing the standard file icons with automatically generated icons that reflect the contents of the files in a principled way. We call such icons Intelligent Icons. While there is little utility in examining an individual icon, examining groups of them provides a greater possibility of unexpected and serendipitous discoveries. The utility of Intelligent Icons can be further enhanced by arranging them on the screen in a way that reflects their similarity/differences. We demonstrate the utility of our approach on data as diverse as DNA, text files, electrocardiograms, and Space Shuttle telemetry. In addition we show that our system is unique in also supporting fast and intuitive similarity search.</p>
      </abstract>
    </article-meta>
  </front>
</article>
