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Design Automation System for Review Analysis Affiliation for Online Educator Reliability Prediction

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Advances in Computer Science and Ubiquitous Computing (CUTE 2018, CSA 2018)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 536))

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Abstract

In this paper, we designed a review analysis automation system to grasp the credibility of the online education matching platform. Web crawling collects and parses reviews and ratings of educators who are atypical data. We will build an emotional dictionary based on the educational field to grasp online educator credibility using collected review data and SO-PMI. We also propose a method for building large - scale learning data based on the emotion dictionary constructed. We proposed a system that provides more reliable review analysis results by measuring the accuracy of emotion dictionary by using deep learning in constructed learning data and evaluation data. Through this, we intend to help judge the credibility of educator in O2O education matching.

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Acknowledgement

This research is supported by Ministry of Culture, Sports and Tourism (MCST) and Korea Creative Content Agency (KOCCA) in the Culture Technology (CT) Research & Development Program 2018 (R2018020083).

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Authors and Affiliations

  1. Department of Computer Engineering, Hoseo University, Asan, South Korea

    Kihoon Lee & Nammee Moon

  2. Center for Business Art, Ewha Womans University, Seoul, South Korea

    Hyogun Kym

Authors
  1. Kihoon Lee
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  2. Hyogun Kym
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  3. Nammee Moon
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Corresponding author

Correspondence to Nammee Moon .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, Korea (Republic of)

    James J. Park

  2. Department of Computer Software Engineering, Soon Chun Hyang University, Asan, Korea (Republic of)

    Doo-Soon Park

  3. Department of Multimedia Engineering, Dongguk University, Seoul, Korea (Republic of)

    Young-Sik Jeong

  4. Department of Computer Science, Georgia State University, Atlanta, GA, USA

    Yi Pan

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Lee, K., Kym, H., Moon, N. (2020). Design Automation System for Review Analysis Affiliation for Online Educator Reliability Prediction. In: Park, J., Park, DS., Jeong, YS., Pan, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2018 2018. Lecture Notes in Electrical Engineering, vol 536. Springer, Singapore. https://doi.org/10.1007/978-981-13-9341-9_52

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  • DOI: https://doi.org/10.1007/978-981-13-9341-9_52

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9340-2

  • Online ISBN: 978-981-13-9341-9

  • eBook Packages: EngineeringEngineering (R0)

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