数据采集与处理2018，Vol.33Issue(3)：496-503,8.DOI:10.16337/j.1004-9037.2018.03.013
基于多核学习的协同滤波算法
Collaborative Filtering Algorithm Based on Multiple Kernel Learning
摘要
Abstract
As a frequently personalized recommendation algorithm of the currently recommendation sys-tem ,collaborative filtering uses the item evaluation by the approximate users to recommend .Kernel function is an approach for non-linear pattern analysis problems .Ordinarily ,collaborative filtering will choose some different kernel functions to analyse the influence between the users .Since the single kernel function can not be adapted to the complicated and various scene ,the combination of multiply kernel function becomes a solution .In terms of scenes ,multiply kernel learning can combine every kernel func-tion for a better result .This paper proposes a collaborative filtering algorithm based on multiple kernel learning .Based on the available kernel function ,this algorithm optimizes the weights of every kernel function to match the data distribution .The experimental result on dianping dataset and foursquare data-set shows that compared with the collaborative filtering algorithm based on common similarity ,the col-laborative filtering algorithm based on multiple kernel learning achieves better performance .That is , multiple kernel learning has a better common adaptation .关键词
协同滤波/多核学习/随机梯度/个性化推荐Key words
collaborative filtering/multiple kernel learning/stochastic gradient/personalized recommen-dation分类
信息技术与安全科学引用本文复制引用
宋恺涛,彭甫镕,陆建峰..基于多核学习的协同滤波算法[J].数据采集与处理,2018,33(3):496-503,8.基金项目
江苏省"六大人才高峰"资助项目. （）
