A Proposed Framework for Automated Online Question and Answering System for Interview using Latent Semantic Analysis

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collectionurl https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
date 2017-07-28 09:52:34
eventvenue Batu Ferringhi, Pulau Pinang
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originalfilename 1559-01-FH03-FIK-17-09889.pdf
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spelling 6882 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6882 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper application/pdf 7 1.6 Adobe Acrobat Pro DC 20 Paper Capture Plug-in Userâ„¢ 2017-07-28 09:52:34 1559-01-FH03-FIK-17-09889.pdf UniSZA Private Access A Proposed Framework for Automated Online Question and Answering System for Interview using Latent Semantic Analysis Interview is an important process to select the best applicant during employee selection process for a company, student enrollment in university and others. The interview process is conducted to find out more about respondent knowledge, personality and background. Interview can be conducted by face to face interview session or online interview session. Online interview session can be structured or unstructured Question and Answer (Q&A). Online interview tends to use structured Q&A where candidates are not given a chance to reveal their knowledge. Because of limitations in the structured online interview, unstructured online interviews started being used by many organizations. However, using unstructured online interviews, it is difficult to determine accuracy of comparing the answer. In this research, we proposed a framework for automated online interview system using Latent Semantic Analysis (LSA) to evaluate the answer. This research will used Natural Language Processing techniques to pre-process the answer and LSA to evaluate the answer. Further in this study, the result of this process will be evaluated and compared with the expert evaluation to grade the answer. The 5th International Conference on Artificial Intelligence, Computer Science, & Information Technology Batu Ferringhi, Pulau Pinang
spellingShingle A Proposed Framework for Automated Online Question and Answering System for Interview using Latent Semantic Analysis
summary Interview is an important process to select the best applicant during employee selection process for a company, student enrollment in university and others. The interview process is conducted to find out more about respondent knowledge, personality and background. Interview can be conducted by face to face interview session or online interview session. Online interview session can be structured or unstructured Question and Answer (Q&A). Online interview tends to use structured Q&A where candidates are not given a chance to reveal their knowledge. Because of limitations in the structured online interview, unstructured online interviews started being used by many organizations. However, using unstructured online interviews, it is difficult to determine accuracy of comparing the answer. In this research, we proposed a framework for automated online interview system using Latent Semantic Analysis (LSA) to evaluate the answer. This research will used Natural Language Processing techniques to pre-process the answer and LSA to evaluate the answer. Further in this study, the result of this process will be evaluated and compared with the expert evaluation to grade the answer.
title A Proposed Framework for Automated Online Question and Answering System for Interview using Latent Semantic Analysis
title_full A Proposed Framework for Automated Online Question and Answering System for Interview using Latent Semantic Analysis
title_fullStr A Proposed Framework for Automated Online Question and Answering System for Interview using Latent Semantic Analysis
title_full_unstemmed A Proposed Framework for Automated Online Question and Answering System for Interview using Latent Semantic Analysis
title_short A Proposed Framework for Automated Online Question and Answering System for Interview using Latent Semantic Analysis
title_sort proposed framework for automated online question and answering system for interview using latent semantic analysis