A Movie Trailer Recommendation System Based on Pre-trained Vector of Relationship and Scenario Content Discovered from Plot Summaries and Social Media

Chun Yu Chien, Guo Hao Qiu, Wen Hsiang Lu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Posting articles on the social platform is the favorite activity of young people. With the potential of digital movie and tv series industry, developing an automatic movie recommendation engine becomes a popular issue. Traditionally movie recommendation is based on structured information like director, players, rough class, etc. Recently, there are more and more researches trying to make a recommendation based on context information like music recommendation based on lyrics with the word vector representation. However, in the long text scenario, the recommendation based on all context vector makes the inference very imprecise.In this paper, we propose effective features types, relationships, and scenarios, to extract important information then improve the recommendation. Furthermore, comparing different pre-training model, we try to maximize the effectiveness of semantic understanding and make the recommendation be able to reflect meticulous perception on the relationship between social media articles and movie plot.

Original languageEnglish
Title of host publicationProceedings - 2019 International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728146669
DOIs
Publication statusPublished - 2019 Nov
Event24th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019 - Kaohsiung, Taiwan
Duration: 2019 Nov 212019 Nov 23

Publication series

NameProceedings - 2019 International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019

Conference

Conference24th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019
CountryTaiwan
CityKaohsiung
Period19-11-2119-11-23

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction

Cite this

Chien, C. Y., Qiu, G. H., & Lu, W. H. (2019). A Movie Trailer Recommendation System Based on Pre-trained Vector of Relationship and Scenario Content Discovered from Plot Summaries and Social Media. In Proceedings - 2019 International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019 [8959918] (Proceedings - 2019 International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TAAI48200.2019.8959918