Big Data Analysis of TV Dramas Based on Machine Learning

被引：0
|
作者：
Tan, Jiaqi [1 ]
Mao, Feiqiao [1 ]
Yang, Lianghai [1 ]
Wang, Jiahui [1 ]
机构：
[1] Shenzhen Univ, Nanhai Ave 3688, Shenzhen 518060, Guangdong, Peoples R China
来源：
SMART COMPUTING AND COMMUNICATION, SMARTCOM 2017 | 2018年 / 10699卷
关键词：
Machine learning; Big data; TV dramas; Predict score; Staring ranking;
D O I：
10.1007/978-3-319-73830-7_9
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Currently, large amount of TV dramas has overwhelmed the demand of TV station which had caused massive waste of resources. This article offers several practical solutions to tackle the above-mentioned problems through building model based on machine learning. Firstly, we build a TV score prediction model with regression and machine learning to rank the most welcomed TV drama. Moreover, we write an Internet worm to collect data from the internet, and build a Star popularity index prediction model by machine learning and regression. And list the much-acclaimed stars based on the popularity index. In conclusion, with the predict score of the TV drama predicted based on machine learning, it can provide a reference for TV station to manage TV programs and with the starring ranking it can help TV drama production team to produce TV dramas in a high quality.
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页码：90 / 95
页数：6
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