Deep learning-based target customer position extraction on social network

In this paper, we extract the target customer attributes and analysis the characteristics of their interests. We classify the accounts into, for example, three data sets, the real estate, healthy parenting and sports. we extract the target customer attributes via deep learning method to study that attributes and build a classification model which is helpful for merchants to find the target customers and make the marketing strategies on social network. We use deep learning method by studying a nonlinear network structure, to achieve complex function approximation and characterization of the input data distribution. We show the strong ability of a few sample concentrated study the data and essential characteristics. The experimental results also show that the DBN outperforms better than the Naïve Bayes classifier.