Television advertising household push and operational analysis

Designing efficient advertising push and auction mechanisms is the key to improving the efficiency and profitability of television stations. Propose by use user-based collaborative filtering algorithm. Firstly, add the scaling variable to optimize the algorithm, and establish a static model for user advertising matching push. Then add the time dimension and build a multi-dimensional push update model to update the recommended advertisings. Finally, propose to use the advertising value to estimate the reasonable reserve price of the advertisement position auction, and use the generalized second price principle to establish the bidding transaction model of the advertisement position. The level of root mean square error indicates that the established multidimensional advertising recommendation model has good recommendation quality. The simulation results show that the incentive bidding mechanism of the generalized second price can effectively increase the seller's profit.