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The implementation of movies and TV plays analysis system combined with knowledge graph and data visualization

  • Fan Yang
    ,
  • Yong Yue
    ,
  • Gangmin Li
  • Xi'an Jiaotong-Liverpool University
Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
 Peer-review

Abstract

More and more movies and television plays have been produced in recent years, but a few have succeeded in the market. Therefore, the analysis and speculation of the success factors of movies and television plays are very important for the producers and investors. The existing analysis platform only analyzes the benefits generated by movies and television dramas in a certain period and lacks the ability of prediction and reasoning. To analyze the key factors affecting the success of movies and television dramas and provide a reference for producers and investors, we design and implement a movies and television plays analysis system combined with a knowledge graph and data visualization technology. First of all, we crawl the information of movies and television plays and user comments on the Douban website; Then, the entities and relationships are extracted by OpenUE toolkit, and Neo4j is used to construct and store the knowledge graph in movies and television plays. On this basis, we utilize the improved TransR algorithm for knowledge completion and reasoning. Finally, combined with the knowledge graph, we analyze the success factors of popular movies and TV plays and visualize the analysis results in various chart types.

Publication Information

Output type

Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
 Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 422-426 (5 pages)

Publication milestones

  • Published - 17/08/2022

Publication status

Published - 17/08/2022

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

Publication series

  • Publication series name: Proceedings - 2022 International Conference on Computer Engineering and Artificial Intelligence, ICCEAI 2022

ISBN (Print)

9781665468046

ISBN (Electronic)

9781665468039

Publication IDs

  • handle.net: 10547/625920
  • Scopus: 85137172486

Host publication title

Proceedings - 2022 International Conference on Computer Engineering and Artificial Intelligence, ICCEAI 2022

Host publication editors

  • Pan Lin
  • Yong Yang

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