Abstract

According to the statistical analysis of the user viewing pay channels behavior based on RFML Model and Pay-TV channel promotion strategy research, build an optimization model. First of all, use the results of RFML model about user viewing behavior and build 0-1 programming model. Secondly, solve the problem by the greedy dynamic programming algorithm while comparing the results to determine the optimal solution for each channel premium channels users. Finally, clustering analysis, the optimal solution for all users to cluster, given the optimal combination of design program results. The results showed that: RFML model results to calculate a single and comprehensive index, and further shows the current users of the program package with premium channel slower satisfaction with the status 0-1 programming model for solving dynamic programming algorithm results show that high clustering results indicate 42 premium channels clustered into four groups show package ideal; CCTVFY type of program can be packaged separately; fishing and sports programs as class program package appropriate; photography, travel, painting Finance, for a small minority of users.

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