关键词: Spark, 推荐算法, ALS模型, 隐性因子, 遗忘函数

Abstract: The recommendation system can provide personalized recommendation services to users based on the user’s basic information and behavior analysis. Therefore, the recommendation system has become a research hotspot in recent years. This paper studies on the algorithm of collaborative filtering recommendation based on ALS model. The implementation of the algorithm uses a distributed platform, and the experimental results show that compared with the previous single-node implementation, the proposed algorithm has greatly improved the computational speed. In addition, this paper reduces the attribute information loss of invisible factor on the loss function, and introduces the interest forgetting function in the predictive score obtained by the optimal model. The experimental comparison shows that the optimized algorithm effectively improves the accuracy of the recommended system.

Key words: Spark, recommendation algorithm, ALS model, hidden factor, forgetting function