UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 6
June-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRCO06020


Registration ID:
216116

Page Number

94-97

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Title

Analytical feature extraction for Individual assessment through Machine Learning in Interface based Interview

Abstract

This paper presents a review on various techniques on predicting the interview performance autonomously using machine learning techniques and analyze the audio-visual features using an interface-based video interview by a virtual agent. Different scenarios are studied and compared for a better understanding of human behavior in case of the video interview. In this paper, the existing optimization techniques are reviewed according to their methodologies and advantages. Based on the review, research gaps are observed and the references are provided for further research work.

Key Words

Interface based video interviews, Automatic job prediction, Machine learning for job prediction, Nonverbal behavior prediction, Regression, Deep learning for audio-visual predictions.

Cite This Article

"Analytical feature extraction for Individual assessment through Machine Learning in Interface based Interview", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.94-97, June-2019, Available :http://www.jetir.org/papers/JETIRCO06020.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Analytical feature extraction for Individual assessment through Machine Learning in Interface based Interview", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp94-97, June-2019, Available at : http://www.jetir.org/papers/JETIRCO06020.pdf

Publication Details

Published Paper ID: JETIRCO06020
Registration ID: 216116
Published In: Volume 6 | Issue 6 | Year June-2019
DOI (Digital Object Identifier):
Page No: 94-97
Country: Bikaner, Rajasthan, India .
Area: Engineering
ISSN Number: 2349-5162


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