Movie Data Analysis and a Recommendation Model
- DOI
- 10.2991/978-94-6463-030-5_74How to use a DOI?
- Keywords
- Visualization; Box Office; Movie Recommendation
- Abstract
The high-risk nature of the movie industry has kept companies looking for better plans to make and invest in a film. With the deepening of Internet applications, it’s possible to clearly visualize and demonstrate the overview of the film market and the performance of different movie genres with their unique features in the market. The box office is an important indicator to measure movie performance, and it to some extent reflects the economic development of modern society. So, explore the rules of box office and its correlation with other features of the film. Moreover, to establish a recommendation model, by vectorizing and attaching values to characteristics of the films, the distance between two movies can be calculated to find similar movies. Thus, suggestions on preparing budget, choosing genre and casting could be given to the film producer based on these historical movie data so as to achieve higher audience reviews and financial returns.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Hang Yang AU - Yiqing Pei AU - Zhihui Wang PY - 2022 DA - 2022/12/20 TI - Movie Data Analysis and a Recommendation Model BT - Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022) PB - Atlantis Press SP - 739 EP - 751 SN - 2589-4919 UR - https://doi.org/10.2991/978-94-6463-030-5_74 DO - 10.2991/978-94-6463-030-5_74 ID - Yang2022 ER -