基于影响强度的社会网络搜索算法研究  

Social Network Searching Algorithm Based on the Strength of Influence

作　　者：惠淑敏[1] 

机构地区：[1]浙江师范大学图书馆,金华321004

出　　处：《图书情报工作》2012年第2期111-115,共5页Library and Information Service

基　　金：浙江省自然科学基金项目"基于复杂网络的电子商务平台演化建模和定价机制研究"(项目编号:Y6110018);浙江师范大学校级项目"基于RSS订阅的协同过滤与推荐机制研究"(项目编号:JYGL201028)研究成果之一

摘　　要：目前大部分社会网络搜索算法都基于最短路径原则,忽视社会网络上主体之间社会关系的强度和方向,导致搜索结果不能很好地满足用户需求。考虑到影响强度在社会网络上的重要作用,提出最大影响强度的路径优化原则,并基于该原则构造搜索算法。运用真实社会网络的数据,验证基于最大影响强度的路径优化算法优于基于最短路径的优化算法,即使在两者路径长度相等的情况下,前者的搜索效果也比后者更好。When searching for a person throngh online social network, currently the most used searching algorithms are based on the principle of the shortest path, which ignores the strength and direction of influence among agents in social network. This leads to the search results being not good enough to meet users＇ needs. Considering the strength of influence playing an important role in social net- work, the path optimization principle of maximizing influence strength is proposed, and a search algorithm based on the principle is constructed. Using network data from real world social network, it is validated that the maximized influence strength of path optimiza- tion algorithm is superior to the optimization algorithm based on the shortest path, even in the case of the two paths being equal length, the performance of the former searching algorithm is better than that of the latter algorithm.

关 键 词：社会网络 影响强度 搜索算法 

分 类 号：G354[文化科学—情报学]