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                <text>Conference Papers</text>
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    <name>Conference Paper</name>
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              <text>SemKnowNews: A Semantically Inclined Knowledge Driven Approach for Multi-source Aggregation and Recommendation of News with a Focus on Personalization</text>
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          <name>Subject</name>
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              <text>News recommendation; Ontology; Personalization; Transformers</text>
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              <text>The availability of digital devices has increased throughout the world exponentially owing to which the average reader has shifted from offline media to online sources. There are a lot of online sources which aggregate and provide news from various outlets but due to the abundance of content there is an overload to the user. Personalization is therefore necessary to deliver interesting content to the user and alleviate excessive information. In this paper, we propose a novel semantically inclined knowledge driven approach for multi-source aggregation and recommendation of news with a focus on personalization to address the aforementioned issues. The proposed approach surpasses the existing work and yields an accuracy of 96.62%  2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.</text>
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          <name>Creator</name>
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              <text>Chhatwal G.S.; Deepak G.; Sheeba Priyadarshini J.; Santhanavijayan A.</text>
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              <text>Communications in Computer and Information Science, Vol-1788 CCIS, pp. 263-274.</text>
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              <text>Springer Science and Business Media Deutschland GmbH</text>
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              <text>2023-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1007/978-3-031-27609-5_21" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-3-031-27609-5_21&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151049057&amp;amp;doi=10.1007%2F978-3-031-27609-5_21&amp;amp;partnerID=40&amp;amp;md5=d15494200d052b1070b35d2aed2f9ad0" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151049057&amp;amp;doi=10.1007%2f978-3-031-27609-5_21&amp;amp;partnerID=40&amp;amp;md5=d15494200d052b1070b35d2aed2f9ad0&lt;/a&gt;</text>
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          <name>Rights</name>
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              <text>Restricted Access</text>
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              <text>ISSN: 18650929; ISBN: 978-303127608-8</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>Chhatwal G.S., Department of Electronics and Communication Engineering, University Institute of Engineering and Technology, Panjab University, Chandigarh, India; Deepak G., Department of Computer Science and Engineering, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India; Sheeba Priyadarshini J., Department of Data Science, CHRIST (Deemed to be University), Bangalore, India; Santhanavijayan A., Department of Computer Science and Engineering, National Institute of Technology, Tiruchirappalli, Tiruchirappalli, India</text>
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