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.

引用

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页码：90 / 95

页数：6

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