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新闻事件的分布式混合推荐算法
引用本文:牛振东,王帅,王诗航,陈杰.新闻事件的分布式混合推荐算法[J].北京理工大学学报,2017,37(7):721-726.
作者姓名:牛振东  王帅  王诗航  陈杰
作者单位:北京理工大学计算机学院,北京 100081;北京市海量语言信息处理与云计算应用工程技术研究中心,北京 100081;北京理工大学计算机学院,北京,100081
基金项目:国家自然科学基金资助项目(61370137)
摘    要:针对新闻的个性化服务差及推荐效率低的问题,提出了一种新闻事件的分布式混合推荐算法.该算法改进了传统的层次聚类算法用于新闻事件发现,通过协调簇中心距离和簇间最远距离的权重解决了传统层次聚类中的大簇问题;使用混合推荐算法进行事件推荐,引入了事件的多重特征来计算用户兴趣模型,更准确地表示用户的兴趣偏好;采用Spark分布式计算平台实现该算法,可处理大数据的个性化推荐问题.在公开数据集上的实验结果表明本文方法有效. 

关 键 词:Spark  分布式  层次聚类  用户兴趣模型  混合推荐
收稿时间:2015/11/5 0:00:00

Distributed News Event Hybrid Recommendation Approach
NIU Zhen-dong,WANG Shuai,WANG Shi-hang and CHEN Jie.Distributed News Event Hybrid Recommendation Approach[J].Journal of Beijing Institute of Technology(Natural Science Edition),2017,37(7):721-726.
Authors:NIU Zhen-dong  WANG Shuai  WANG Shi-hang and CHEN Jie
Institution:1. School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China;2. Beijing Engineering Research Center of Massive Language Information Processing and Cloud Computing Application, Beijing 100081, China
Abstract:A distributed news event hybrid recommendation approach was proposed to improve efficiency of personalized news recommendation.In this approach,the traditional hierarchical cluster algorithm was modified to find news events,the distance weight of two cluster centers and the maximum distance weight among different clusters were modulated to avoid'big cluster'in traditional hierarchical cluster.Then a hybrid recommendation algorithm was used to recommend news events,and a users' interest model with multiple event characteristics was introduced into the hybrid recommendation algorithm.At last,this approach was implemented with Spark to deal with big data recommendation.Experimental results on open collections show the effectiveness of our proposed approach.
Keywords:Spark  distribution  hierarchical cluster  user interest model  hybrid recommendation
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