Network Literature Recommendation Technology Based on User-Based Collaborative Filter

With the development of web2.0, network literature website has become an import carrier of publishing literature and getting novel. At present, the increasing of the number of network literature brings great confusion for audience. Therefore, network literature website need to recommend potential interested literature according to readers’ different requirements to take full advantage of resource and provide personalized services. The thesis we use the user-based collaborative algorithm to recommend readers for interested literature. We analysis the influence of k-value on recommend result and utilize kinds of Measurements to evaluate the results.