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    <title>non-Boolean lattice</title>
    <link>http://popups.lib.uliege.be/1373-5411/index.php?id=3773</link>
    <description>Index terms</description>
    <language>fr</language>
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      <title>Modeling of Changing Logical Structures when Unanticipated Information Emerges</title>
      <link>http://popups.lib.uliege.be/1373-5411/index.php?id=3078</link>
      <description>Anticipation involved in our reading process deepens our experience, supporting the sense of understanding, suspense, and surprise. Rough set driven lattice is a suitable tool for analyzing subjective phenomenon such as reading because 1) it produces Boolean as well as non-Boolean lattices that reflect the input information, and 2) this method requires two interpretations of a target, such as subject and attribute, which a sentence provides. By using this method, we can compare how a logical structure resulting from reading with anticipation is different from the information revealed by the actual text. The difference is quantified by complement properties of a lattice, through complementarity and non-distributivity. </description>
      <pubDate>Fri, 06 Sep 2024 16:07:28 +0200</pubDate>
      <lastBuildDate>Tue, 08 Oct 2024 14:18:35 +0200</lastBuildDate>
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    <item>
      <title>Model of Figure-Ground Cognition in Literary Text</title>
      <link>http://popups.lib.uliege.be/1373-5411/index.php?id=3772</link>
      <description>Cognitive mechanisms and nerve systems are an important issue in the phylogeny of living organisms. Human consciousness has long been studied, with various models being developed, and the discussion still continues today. Originally generated for visual perception, gestalt psychology introduced the idea of figure and ground to describe our mechanism of attention. We have come up with a method to model such figure and ground relation. We have applied this method to model how a figure and ground relation may be applied to story characters when reading a literary work. We compared this result with a control resulting from randomly generated input matrix. The resulting graph generated from text has characteristics changes. The changes in the graph reflect a dramatic shift in character attributes. Such drama may encourage the reader to anticipate what comes next in the story. </description>
      <pubDate>Mon, 30 Sep 2024 14:07:39 +0200</pubDate>
      <lastBuildDate>Mon, 30 Sep 2024 14:07:48 +0200</lastBuildDate>
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