基于项的协同过滤在推荐系统中的应用研究

Research on application of item-based collaborative filtering in recommender systems

分析基于项的协同过滤在推荐系统中应用及所存在的问题,提出了一个基于项的协同过滤改进算法,并给出了改进算法在标准数据集上的实验结果,对改进算法与原算法进行了相关性能的比较分析,证明了改进算法的有效性。最后,对研究进行了总结,指出存在的不足,提出了进一步研究的方向。

It analyzes application of item-based collaborative filtering in E-commerce recommender systems and the problems which item-based collaborative filtering is facing when it is applied in recommender systems. An improved method of item-based collaborative filtering algorithm is proposed. It is theoretically detailed analyzed and proved its feasibility. Then the experimental results that the new method is implemented with the benchmark experimental data set are given, the performance between the new method and the old one is compared and analyzed and the new method is proved valid. Finally, the research is summarized, some defects and the directions that will be further studied in the future.