A Potential Friend Recommendation System Based on Classification Algorithm

A potential friend recommendation system based on classification algorithm is proposed. The system uses the two-step feature method to process the original data set and removes irrelevant features for the classifier. The potential problems of scholars are translated into two classification problems. By comparing the classification effect of four commonly to find out the best classifier, the method of classifiers in two-step feature selection is used. At the same time, it concludes six influence factors and main diffusion characteristics. The social network information from the Academic Social Network (SCHOLAT) is tested as the original data sets. The experiment shows that the method based on significantly improves the accuracy and the F1 value. It reflects the accuracy and practical value of the recommendation system of potential friends based on classification algorithms.