论文摘要
基于truss模型的社区查询问题是根据给定的查询结点q以及参数k,返回包含查询结点的所有k-truss社区。随着信息技术的发展,网络用户数量的爆发式增长,社区查询问题在学术领域开始被广泛关注,而因为truss模型可以很好的模拟现实世界中网络社区的特性,因此可以通过truss模型解决社区查询的问题。然而,目前现有的社区查询方法存在因冗余操作导致查询效率低的问题。本文针对基于truss模型的社区查询问题进行研究,具体研究内容如下。首先,在创建索引阶段,提出一种基于truss等价的索引构建方法。该方法直接在原始图中将边界边所在的超级结点标记到自身的supnode属性中,作为创建超级边的前提,进而创建索引。与现有算法相比,该方法无需对原始边进行边trussness值相等的集合划分,在创建超级边时避免了对超级结点的冗余遍历操作,从而能够快速完成超级边的创建,加速整个索引的创建过程。其次,在k-truss社区查找阶段,提出一种高效的k-truss社区查询方法。该方法在已有索引结构的基础上,通过使用基于散列表的快速定位技术,在不丢失原始边的前提下,可以快速定位到查询结点所在的超级结点集合,并设计了相关的社区查询策略,提升了社区查询的处理效率。最后,通过在多组真实数据集上进行比对测试,分别从创建索引的时间、社区查询的时间以及k值对社区查询的影响进行比较和分析,通过实验结果验证了所提算法方案的有效性和高效性。
论文目录
文章来源
类型: 硕士论文
作者: 祝海燕
导师: 陈子阳,徐凤东
关键词: 社区查询,索引
来源: 燕山大学
年度: 2019
分类: 基础科学,信息科技
专业: 数学,计算机软件及计算机应用
单位: 燕山大学
分类号: O157.5;TP301.6
DOI: 10.27440/d.cnki.gysdu.2019.000538
总页数: 56
文件大小: 1236K
下载量: 24
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