Advertising Recommendation Application Based on KMeans-LR
With the rapid development of the Internet and online advertising business,in the face of massive and sparse advertising click log data,the single traditional prediction method has poor performance in massive advertising data recommendation due to its low performance.This paper proposes an advertising recommendation model based on cluster-logic regression(KMeans-LR).The model first normalizes the probability of each column of the initial data through the Softmax function,and constructs and processes each column value as the classification probability value.Then it is input into KMeans algorithm,and control the number of categories through hyper-parameters for automatic classification;Finally,it is input into the segmented logistic regression model for prediction.Compared with traditional FM and logistic regression algorithms,the experiment on open data sets has better performance.
Multidimensional clusteringLogical regressionFeature processingIntelligent recommendationAI and intelligent manufacturing
万方数据
维普
