基于启发式函数的分布式FN算法  

Distributed FN Algorithm Based on Heuristic Function

作　　者：肖有诰[1] 屠成宇[1] 

机构地区：[1]江南计算技术研究所,无锡214083

出　　处：《计算机系统应用》2012年第10期122-125,共4页Computer Systems & Applications

摘　　要：对复杂网络进行社团挖掘和分析是很多领域和学科的重要问题,结合海量数据通联矩阵稀疏的特点,提出了一种基于启发式函数合并的快速社团挖掘算法KFN算法,并建立了算法的MapReduce模型.通过对DBLP论文合著网络数据集进行挖掘可知,分布式模型和基于启发式函数的合并策略能够提高社团挖掘的时间效率.The mining and analysis of community in complex networks is an important issue in many domains and disciplines. In this paper, focus on the sparsy Communication Matrix of the massive data, we suggest a fast mining algorithms based on a heuristic function to merge called KFN algorithm, and also show out the MapReduce model of this algorithm. With experiment focued on the DBLP paper co-network data sets, we conclude that distributed mining model and the merging strategy based on the heuristic function can improve, the time efficiency on community mining.

关 键 词：海量数据 社团挖掘 启发式函数 MAPREDUCE 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]