Simulation Resource Recommendation System Based on Collaborative Filtering

The present simulation resource management systems are full of all kinds of simulation resources; it is inefficient to get the needed simulation resource with the traditional search methods. To solve this problem, the recommendation system based on collaborative filtering is applied to the simulation resource management system, which can recommend the most relative simulation resource to the user according to user's previous preference. After analyzing the necessity of combining the recommendation system with the simulation resource system, the simulation resource recommendation system is designed and realized. The realization includes three main procedures: collecting user preferences, finding neighbor users, recommending simulation resources. The recommendation system collects users' grading on used simulation resources as user preferences, and uses the Pearson correlation to calculate the similarity between users and then finds out the neighbor users; then it bases on the neighbor users to predict the user's grade of the resource and then gets the recommended resources. The test result shows that the recommended resources have strong similarity with the user' previous preference. The recommendation system improves the efficiency of the resource obtaining and the use frequency of the recommended resource.