Design And Implementation Of Novel Personalized Recommendation System Based On User Behavior

With the development of the times,novel reading has gradually shifted from the era of paper reading to the era of electronic reading,and the content of electronic novels has gradually become overloaded with information.As a novel reader,you are more concerned about how to find your favorite content from a large number of novel contents;as a novel website,you need to consider how to distribute the content of your platform better,so as to maximize benefits;as a novel creator,you need to consider how to make your high-quality works get more traffic,so as to attract more people’s attention and realize personal value.A personalized novel recommendation system based on user behavior can solve the above contradictions very well.On the one hand,it can meet the personal reading needs of novel users through personalized recommendation,and on the other hand,it can distribute the works of novel creators according to the interests of readers.Not just relying on popularity distribution,it greatly guarantees the flow of works of novel creators.In this way,the dependence of novel users and novel creators on the novel platform can be ensured to a certain extent,thereby improving the overall efficiency of the novel platform,and achieving a win-win situation for novel readers,novel websites and novel creators.In view of the above analysis,this paper designs and implements a personalized novel recommendation system based on user behavior.By mining the historical operation behavior data of novel users on the platform,analyze the novels that users may be interested in but have no operation behavior to recommend to them,so as to meet the personalized needs of novel users.The recommended amount guarantees the creative enthusiasm of novel creators.