吉林大学学报（信息科学版）2013，Vol.31Issue(4)：359-364,6.
基于Hadoop的社交网络服务推荐算法
Algorithm for Social Network Recommendation Service Based on Hadoop
摘要
Abstract
In order to process huge amount of data generated in the social network with efficiency and scalability,we designed the distributed TF-IDF(Term Frequency-Inverse Document Frequency)algorithm suitable for MapReduce,and implemented this algorithm on Hadoop.This algorithm extracts key words in user's weibo,in this way user's interest could be found,and the corresponding service could be recommended to the user.In order to verify the validity and scalability of the distributed TF-IDF algorithm,the results of the distributed TF-IDF algorithm and TextRank algorithm was compared.The experimental results show that key words extracted bythe distributed TF-IDF algorithm could represent characteristics of the user more accurately.By Contrasting the response time,it could be seen that the distributed TF-IDF algorithm has a good scalability.关键词
Hadoop云平台/分布式TF-IDF算法/MapReduce模型/TextRank算法Key words
hadoop/ distributed TF-IDF algorithm/ mapreduce/ textrank algorithm分类
信息技术与安全科学引用本文复制引用
李玲,任青,付园,陈鹤,梅圣民..基于Hadoop的社交网络服务推荐算法[J].吉林大学学报（信息科学版）,2013,31(4):359-364,6.基金项目
吉林省自然科学基金资助项目(201215016) （201215016）
