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

研究成果: Conference contribution

2 引文 斯高帕斯(Scopus)

摘要

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.

原文English
主出版物標題Proceedings - 2019 International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781728146669
DOIs
出版狀態Published - 2019 11月
事件24th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019 - Kaohsiung, Taiwan
持續時間: 2019 11月 212019 11月 23

出版系列

名字Proceedings - 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
國家/地區Taiwan
城市Kaohsiung
期間19-11-2119-11-23

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦科學應用
  • 人機介面

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