A rules extraction algorithm for IPTV customers forecasting based on the forecasting entropy measurement - Minjuan WANG; Zhengpeng JI; Chao LV (Dianxin kexue)
An algorithm model conformed to the user behavior,based on the massive IPTV user characteristic data which extract rules and classify IPTV users was proposed.First,IPTV user group description dimension in accordance with the user on demand was put forward.Namely,the user group could be described by basic property and trend of user behavior could be described by users' demand behavior.Then the concept of prediction measurement was put forward,the stability of user group was described,and an algorithm which extracted demand behavior probability on stable user group was proposed.At last,the algorithm model was verified and analyzed by massive IPTV operation data.