The Study Of Telecommunication Package Recommendation Model Based On Consumer Behavior

With the increase of users’ needs, the telecommunications packages’ marketbecomes more segmented. The designs are more diversified and multi-angle and thefunctions have become even more complete and rich. However, other than bring marketadvantage, the huge amount of new packages caused huge information managementdifficulties to telecom operators, and also gives users too many choices to match theirneeds. To end this, personalized and intelligent package recommendation are especiallyimportant and necessary. It is a trend to obtain useful knowledge from the massiveamounts of data, dynamically analyze user needs, scientifically establish therecommended model, and actively recommend suitable telecommunications packageproducts to consumers.To build Telecommunication package recommendation model based on consumerbehavior, this assay used collaborative filtering, content-based recommendation,personalized recommendation association rules, and clustering analysis. In this assays,first, the author built consumer behavior model of telecom users and the telecompackage information model, and characterized the dimensions and indicators of telecomuser consumer behavior and telecom packages. Then, the author used the user-basedcollaborative filtering to design a “user to telecom package” recommended model, anddesigned a “telecom package to the user” recommendation model with content-basedrecommendation. Finally, based on these two models, the author created a telecompackage recommendation system, and testified the numerical verification and softwareimplementation of the model with the empirical data of a certain city.In this article, personalized recommendation method is introduced to thetelecommunications industry, and a solid theoretical analysis and scientificrecommendation algorithm are used to build a telecommunications packagerecommended model. The practicality and scientificity of this model is confirmed bysoftware implementation and revenue verification of empirical data. This articleprovided scientific and intelligent recommended method and management tools forpackage operation management of telecommunication companies.