Article Details

Abstract

With the rapid development of Internet technology and the popularity of smart set-top boxes, Internet TV has gradually become the key entrance of the living room economy, and users tend to watch specific types of programs and pay for the film and TV series preference. With the help of K-means algorithm to label clustering, this study utilizes Big Data means for user viewing data mining analysis, builds identification multidimensional data labels of user viewing behavior characteristics, and forms Internet TV user portrait of different viewing preferences. It guides operations and maintenance departments to provide differentiated services to specific groups, so as to better meet the common or personalized needs and promote the sustainable development of Internet TV business.

Keywords

Internet TV; user portrait; viewing preference; data analysis

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About the authors

Zhou Wei (1984-), male, Han ethnicity, born in Hohhot, Inner Mongolia, is a senior engineer with a master's degree. His research interests include big data operation analysis, artificial intelligence, and self intelligent networks; Ni Feng (1993-), male, Manchu, from Chifeng, Inner Mongolia, intermediate engineer, master's degree, research direction: artificial intelligence and big data; Meng Liqing (1977-), male, Han ethnicity, from Ulanqab, Inner Mongolia, is a senior engineer with a master's degree. His research interests include microservices, databases, and artificial intelligence; Geng Zhenchun (1989-), male, Han ethnicity, from Ulanqab, Inner Mongolia, senior engineer, master's degree, research direction: artificial intelligence and big data; Wang Junwei (1986-), male, Han ethnicity, from Anyang, Henan Province, assistant engineer, bachelor's degree, research direction: database, big data analysis and mining; Cai Chuankun (1989-), male, ethnic, Han nationality, from Xinyang, Henan, senior engineer, bachelor's degree, research direction: artificial intelligence and big data.