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              <text>Design and Development of Artificial Intelligence Knowledge Processing System for Optimizing Security of Software System</text>
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              <text>Bi-directional encoder representation for transformers; Knowledge processing; Software development; Software security; Software vulnerability</text>
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              <text>Software security vulnerabilities are significant for the software development industry. Exploration is conducted for software development industry landscape, software development eco-system landscape, and software system customer landscape. The focus is to explore the data sources that can provide the software development team with insights to act upon the security vulnerabilities proactively. Across these modules of software landscape, customer landscape, and industry landscape, data sources are leveraged using artificial intelligence approaches to identify the security insights. The focus is also on building a smart knowledge management system that integrates the information processed across modules into a central system. This central intelligence system can be further leveraged to manage software development activities proactively. In this exploration, machine learning and deep learning approaches are devised to model the data and learn from across the modules. Architecture for all the modules and their integration is also proposed. Work helps to envision a smart system for Artificial Intelligence-based knowledge management for managing software security vulnerabilities.  2023, Crown.</text>
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          <name>Creator</name>
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              <text>Althar R.R.; Samanta D.; Purushotham S.; Sengar S.S.; Hewage C.</text>
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              <text>SN Computer Science, Vol-4, No. 4</text>
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              <text>2023-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1007/s42979-023-01785-2" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/s42979-023-01785-2&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152917249&amp;amp;doi=10.1007%2Fs42979-023-01785-2&amp;amp;partnerID=40&amp;amp;md5=49410643b35f8601ff42182d441f50d5" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152917249&amp;amp;doi=10.1007%2fs42979-023-01785-2&amp;amp;partnerID=40&amp;amp;md5=49410643b35f8601ff42182d441f50d5&lt;/a&gt;</text>
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          <name>Rights</name>
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              <text>All Open Access; Hybrid Gold Open Access</text>
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          <description>A related resource</description>
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              <text>ISSN: 2662995X</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>Althar R.R., CHRIST (Deemed to be) University, Karnataka, Bangalore, India, First American India Private Limited, Karnataka, Bangalore, India; Samanta D., CHRIST (Deemed to be) University, Karnataka, Bangalore, India, Department of Computational Information Technology, Rochester Institute of Technology-RIT Global, Germia Campus, Prishtina, Kosovo, 10000; Purushotham S., Department of Information Science, BMS Institute of Technology and Management, Karnataka, Bangalore, India; Sengar S.S., Department of Computer Science, Cardiff Metropolitan University, Cardiff, CF5 2YB, United Kingdom; Hewage C., Department of Computer Science, Cardiff Metropolitan University, Cardiff, CF5 2YB, United Kingdom</text>
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