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Crowdsourcing Platform for Collecting Cognitive Feedbacks from Users: A Case Study on Movie Recommender System

In: Reliability and Statistical Computing

Author

Listed:
  • Luong Vuong Nguyen

    (Chung-Ang University)

  • Jason J. Jung

    (Chung-Ang University)

Abstract

The aim of this research is to present a crowdsourcing-based recommendation platform called OurMovieSimilarity (OMS), which can collect and sharecognitive feedbacks from users. In particular, we focus on the user’s cognition patterns on the similarity between the two movies. OMS also analyzes the collected data of the user to classify the user group and dynamic changes movie recommendations for each different user. The purpose of this is to make OMS interact intelligently and the data collected faster and more accurately. We received more than a thousand feedbacks from 50 users and did the analyzes this data to group the user. A group of the users can be dynamically changed, with respect to the selection of each user. OMS now still online and collecting data. We have been trying to enrich the cognitive feedback dataset including more than 20,000 feedbacks from 5000 users, so that the recommendation system can make more accurate analysis of user cognitive in choosing the movie similarity.

Suggested Citation

  • Luong Vuong Nguyen & Jason J. Jung, 2020. "Crowdsourcing Platform for Collecting Cognitive Feedbacks from Users: A Case Study on Movie Recommender System," Springer Series in Reliability Engineering, in: Hoang Pham (ed.), Reliability and Statistical Computing, pages 139-150, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-030-43412-0_9
    DOI: 10.1007/978-3-030-43412-0_9
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    Cited by:

    1. Giang T. C. Tran & Luong Vuong Nguyen & Jason J. Jung & Jeonghun Han, 2022. "Understanding Political Polarization Based on User Activity: A Case Study in Korean Political YouTube Channels," SAGE Open, , vol. 12(2), pages 21582440221, April.

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