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<item>
  <id>06104172</id>
  <dt>a</dt>
  <an>06104172</an>
  <augroup>
    <au>Chen, Guang</au>
    <au>Zhong, Ning</au>
  </augroup>
  <ti>Three granular structure models in graphs.</ti>
  <so>Li, Tianrui (ed.) et al., Rough sets and knowledge technology. 7th international conference, RSKT 2012, Chengdu, China, August 17--20, 2012. Proceedings. Berlin: Springer (ISBN 978-3-642-31899-3/pbk). Lecture Notes in Computer Science 7414. Lecture Notes in Artificial Intelligence, 351-358 (2012).</so>
  <py>2012</py>
  <pu>Berlin: Springer</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
    <ut>Granular Structures</ut>
    <ut>Graph</ut>
    <ut>Vertex-oriented granulation</ut>
    <ut>Edge-oriented granulation</ut>
    <ut>Combination-oriented granulation</ut>
  </utgroup>
  <cigroup>
  </cigroup>
  <ligroup>
    <li>doi:10.1007/978-3-642-31900-6_44</li>
  </ligroup>
  <abgroup>
    <ab>Summary: The granular structures emphasize a multilevel and multiview understanding of problems. This paper gives a study on how to granulate a graph, and how to extract the granular structures in the graph. There are three kinds of objects in the graph, vertices, edges and the combinations of vertices and edges. Differing from previous researches on graph clustering which focused on the classification of vertices, we study three granular structure models for the three kinds of objects in the graph.</ab>
    <rv></rv>
  </abgroup>
</item>