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            <name>Title</name>
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                <text>Conference Papers</text>
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    <name>Conference Paper</name>
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          <name>Title</name>
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              <text>Conceptual comprehension analysis of a student using soft cosine measure</text>
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          <name>Subject</name>
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              <text>Comprehension; Concept; Cosine Similarity; Natural Language Processing; Soft Cosine Measure</text>
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          <name>Description</name>
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              <text>Knowledge is the substantial wealth of a man and he possesses an innate thirst to acquire it. Knowledge embodies facts or ideas acquired through study, investigation and observation or experience. In this context, technology with its varied techniques comprising endless algorithms in natural language processing (NLP) plays an imperative role in the pursuit of knowledge. Inferences thus gathered are a clear pointer to the content teaching of students. Soft cosine measure algorithm is used in this analysis process to provide an answer regarding the grasping ability of each student with optimum learner participation and creativity. After each lecture, students have to upload their corresponding notes and this in turn would be compared with the teacher's lecture notes. The soft cosine computation gives individual results, on how much each student has comprehended a concept. This new methodology is a much awaited contribution of the educational field.   2022 Author(s).</text>
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          <name>Creator</name>
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              <text>Baby A.; Vaidhehi V.</text>
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          <name>Source</name>
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              <text>AIP Conference Proceedings, Vol-2463</text>
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          <name>Publisher</name>
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              <text>American Institute of Physics Inc.</text>
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          <name>Date</name>
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              <text>2022-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1063/5.0080146" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1063/5.0080146&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129922451&amp;amp;doi=10.1063%2F5.0080146&amp;amp;partnerID=40&amp;amp;md5=82fcd18925b0d223ff9719dfc75c7136" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129922451&amp;amp;doi=10.1063%2f5.0080146&amp;amp;partnerID=40&amp;amp;md5=82fcd18925b0d223ff9719dfc75c7136&lt;/a&gt;</text>
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          <name>Rights</name>
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              <text>All Open Access; Bronze Open Access</text>
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          <name>Relation</name>
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              <text>ISSN: 0094243X; ISBN: 978-073544192-7</text>
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          <name>Format</name>
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              <text>Online</text>
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              <text>English</text>
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          <name>Type</name>
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              <text>Conference paper</text>
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              <text>Baby A., Department of Computer Science, Christ University, Bangalore, 560029, India, Department of Computer Science, Rajagiri College of Social Sciences, Kerala, Kalamassery, 683104, India; Vaidhehi V., Department of Computer Science, Christ University, Bangalore, 560029, India</text>
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