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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>Articles</text>
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    <name>Article</name>
    <description>Faculty Publications -Articles</description>
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        <element elementId="50">
          <name>Title</name>
          <description>A name given to the resource</description>
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              <text>Tangent Search Long Short Term Memory with Aadaptive Reinforcement Transient Learning based Extractive and Abstractive Document Summarization</text>
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        <element elementId="49">
          <name>Subject</name>
          <description>The topic of the resource</description>
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              <text>Feature Selection; Improved Reinforcement Learning; Knowledge Graph; Optimization Technique; ROUGE Scores; Summarization</text>
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          <name>Description</name>
          <description>An account of the resource</description>
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              <text>Text summarization is the process of creating a shorter version of a longer text document while retaining its most important information. There have been a number of methods proposed for text summarization, but the existing method does not provide better results and has a problem with sequence classification. To overcome these limitations, a tangent search long short term memory with adaptive reinforcement transient learning-based extractive and abstractive document summarization is proposed in this manuscript. In abstractive phase, the features of the extractive summary are extracted and then the optimal features are selected by Adaptive Flamingo Optimization (AFO). With these optimal features, the abstractive summary is generated. The proposed method is implemented in python. For extractive text summarization, the proposed method attains 42.11% ROUGE-1 Score, 23.55% ROUGE-2 score and 41.05% ROUGE-L score using Gigaword. Additionally, 57.13% ROUGE-1 Score, 28.35% ROUGE-2 score and 52.85% ROUGE-L score using DUC-2004 dataset. For abstractive text summarization the proposed method attains 47.05% ROUGE-1 Score, 22.02% ROUGE-2 score and 48.96% ROUGE-L score using Gigaword. Also, 35.13% ROUGE-1 Score, 20.35% ROUGE-2 score and 35.25% ROUGE-L score using DUC-2004 dataset. 2023, Modern Education and Computer Science Press. All rights reserved.</text>
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        <element elementId="39">
          <name>Creator</name>
          <description>An entity primarily responsible for making the resource</description>
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            <elementText elementTextId="99525">
              <text>Rajan R.P.; Jose D.V.; Gurumoorthy R.</text>
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        <element elementId="48">
          <name>Source</name>
          <description>A related resource from which the described resource is derived</description>
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            <elementText elementTextId="99526">
              <text>International Journal of Modern Education and Computer Science, Vol-15, No. 6, pp. 56-72.</text>
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          <name>Publisher</name>
          <description>An entity responsible for making the resource available</description>
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              <text>Modern Education and Computer Science Press</text>
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        <element elementId="40">
          <name>Date</name>
          <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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            <elementText elementTextId="99528">
              <text>2023-01-01</text>
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        <element elementId="43">
          <name>Identifier</name>
          <description>An unambiguous reference to the resource within a given context</description>
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            <elementText elementTextId="99529">
              <text>&lt;a href="https://doi.org/10.5815/ijmecs.2023.06.05" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.5815/ijmecs.2023.06.05&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179341442&amp;amp;doi=10.5815%2Fijmecs.2023.06.05&amp;amp;partnerID=40&amp;amp;md5=c513701902867c7017fab4a5cef53295" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179341442&amp;amp;doi=10.5815%2fijmecs.2023.06.05&amp;amp;partnerID=40&amp;amp;md5=c513701902867c7017fab4a5cef53295&lt;/a&gt;</text>
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        <element elementId="47">
          <name>Rights</name>
          <description>Information about rights held in and over the resource</description>
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            <elementText elementTextId="99530">
              <text>All Open Access; Bronze Open Access</text>
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          </elementTextContainer>
        </element>
        <element elementId="46">
          <name>Relation</name>
          <description>A related resource</description>
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            <elementText elementTextId="99531">
              <text>ISSN: 20750161 | CS; 2023-2024; Vol-1; 00123-00140</text>
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          <name>Format</name>
          <description>The file format, physical medium, or dimensions of the resource</description>
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            <elementText elementTextId="99532">
              <text>Online</text>
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          </elementTextContainer>
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          <name>Language</name>
          <description>A language of the resource</description>
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            <elementText elementTextId="99533">
              <text>English</text>
            </elementText>
          </elementTextContainer>
        </element>
        <element elementId="51">
          <name>Type</name>
          <description>The nature or genre of the resource</description>
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            <elementText elementTextId="99534">
              <text>Article</text>
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          </elementTextContainer>
        </element>
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          <name>Coverage</name>
          <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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            <elementText elementTextId="99535">
              <text>Rajan R.P., Department of Computer Science, Christ (Deemed to be University), S.G. Palya, Karnataka, Bengaluru, 560029, India; Jose D.V., Department of Computer Science, Christ (Deemed to be University), Bangalore, India; Gurumoorthy R., NTT DATA Services, Winnipeg, Canada</text>
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