Design and Implementation of IPTV User Multidimensional Profile Based on User Preference Mining Algorithm
With the growth of users and the development of audio-visual services,IPTV platforms have accumulated massive user behavior data.Accurately mining user preferences in behavioral data is the key to the sustainable development of audio-visual services.According to the characteristics and business scenarios of IPTV users,this paper designs a user preference mining algorithm based on statistical rules and machine learning for IPTV user behavior data,respectively mining the basic and deep preferences of IPTV users.It realizes the combination of basic and deep labels of IPTV user multidimensional portrait through big data technologies such as Hadoop,Hive,and Spark.The research in this paper can provide a basis for media resource value management,customized services,and personalized recommendations.
万方数据
维普
