Simulation research of university library recommended system based on big data and data mining
Rui Li · Advances in computer science research · 2015
This paper based on the specific needs of the university library, analyzes construct necessity, feasibility and technical solutions to select automatic recommendation system for books, and a brief introduction of collaborative filtering algorithms, in particular the correlation calculation and different evaluation criteria.Then nearly 5 million loan offline test history data validate our ideas through the use of the university library, and focused on the specific needs due to the university library, the recommended herein may be based on local search for similar user, saves computing resources and at the same time without sacrificing significant accuracy.Finally, we have also introduced some of the content related to the implementation, including the consideration of a cold start and user interaction design, and lack of presence through the implementation of current research findings.This article provides some practical guidance and reference value for the field of application of the recommendation system of university library.