计算机应用与软件2018，Vol.35Issue(5)：130-134,189,6.DOI:10.3969/j.issn.1000-386x.2018.05.023
基于时间效应与隐语义模型的高校图书馆的个性化推荐研究
RESEARCH ON THE PERSONALIZED RECOMMENDATION OF UNIVERSITY LIBRARY BASED ON TIME EFFECT AND LATENT FACTOR MODEL
摘要
Abstract
In order to select quickly in the mass of books, aiming at the characteristics that university readers have the same knowledge background in different stages of learning, this paper proposed a fusion algorithm based on matrix decomposition of latent factor model and time effect,and made a personalized book recommendation for university books. The algorithm firstly used the stochastic gradient descent method to solve the user -item scoring matrix.Second, an improved solution was proposed to the problem of cold start.Finally,the accuracy of the proposed algorithm was verified by the mean absolute error MAE and the root mean square error RMSE.The results of a large number of experiments verified the feasibility and effectiveness of the algorithm.关键词
推荐系统/隐语义模型/时间效应/冷启动/高校图书馆Key words
Recommendation system/Latent factor model/Time effect/Cold start/University library分类
信息技术与安全科学引用本文复制引用
李薛剑,刘梦雅,海健强,吴雪扬,余雪莉..基于时间效应与隐语义模型的高校图书馆的个性化推荐研究[J].计算机应用与软件,2018,35(5):130-134,189,6.基金项目
安徽大学信息保障协同创新中心开放课题(Y01002454) （Y01002454）
安徽大学大学生科研训练计划项目(201610357400). （201610357400）
