Research on Collaborative Filtering Based on Forgetting Curve
Le Zhang · Computer Knowledge and Technology · 2014
Exploitation With the rapid development of information technology and Internet technology,recommender system has become the important way to solve Information overload.Collaborative filtering because its algorithm is simply,can deal with complex issues and has good effect is widely used by people,also became the most successful recommender system technology.However,the user's interest is always changing,and for new users system cannot predict the user's preference,so to solve this problem,researched on the Ebbinghaus forgetting curve and recommendation algorithm,found that people's interest are constantly changing,and this kind of change is the process of natural forgetting,that is to say,it is keeping with the curve,so applied the forgetting function to simulate the change of user's interest.Taking into account the time playing an important role to score,when using similarity algorithm introduced time factor in it,made a attenuation for the original score of the users.Then designed two groups of experiments to verify the effectiveness of the algorithm.Through two groups of experimental results demonstrated that,generally speaking,the proposed similarity computing method based on the forgetting curve was better than the traditional algorithm.