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              <text>Descriptive Answer Evaluation using NLP Processes Integrated with Strategically Constructed Semantic Skill Ontologies</text>
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              <text>E-Learning; Keyword Extraction; Natural Language Processing; Online Evaluation; Ontology</text>
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              <text>The world is moving towards an online methodology of education. One of the key challenges is the assessment of questions which do not have a definite answer and have several correct answers. To solve this problem, and for quality evaluation of descriptive answers online, an automatic evaluation methodology is proposed in this work. A language model is modelled from the expected answer key, and entity graphs are generated from the ontology modelled using the input answer to be evaluated. Natural Language Processing (NLP) techniques like Stemming, Summarization, and Polarity Analysis are integrated in this work with Ontologies for the efficient evaluation of descriptive answers. Several challenges which come across evaluating descriptive answers are discussed in this chapter, and they have been solved in order to obtain a dynamic and robust evaluating system. Finally, the system is evaluated using a user-feedback methodology comprising a panel of 100 students and 100 professors.  2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)</text>
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              <text>Deepak G.; Ayush Kumar A.; Priyadarshini S.; Singh D.</text>
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              <text>CEUR Workshop Proceedings, Vol-3335, pp. 64-76.</text>
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              <text>Restricted Access</text>
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              <text>ISSN: 16130073</text>
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              <text>Deepak G., Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India; Ayush Kumar A., National Institute of Technology, Tiruchirappalli, India; Priyadarshini S., CHRIST(Deemed to be University), Bangalore, India; Singh D., Birla Institute of Technology and Science, Pilani, India</text>
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