Community search over bipartite graphs has attracted significant interest recently. In many applications such as user-item bipartite graph in E-commerce, customer-movie bipartite graph in movie rating website, nodes tend to have attributes, while previous community search algorithm on bipartite graphs ignore attributes, which makes the returned results with poor cohesion with respect to their node attributes. In this paper, we study the community search problem on attributed bipartite graphs. Given a query vertex q, we aim to find attributed $\left(\alpha,\beta\right)$-communities of $G$, where the structure cohesiveness of the community is described by an $\left(\alpha,\beta\right)$-core model, and the attribute similarity of two groups of nodes in the subgraph is maximized. In order to retrieve attributed communities from bipartite graphs, we first propose a basic algorithm composed of two steps: the generation and verification of candidate keyword sets, and then two improved query algorithms Inc and Dec are proposed. Inc is proposed considering the anti-monotonity property of attributed bipartite graphs, then we adopt different generating method and verifying order of candidate keyword sets and propose the Dec algorithm. After evaluating our solutions on eight large graphs, the experimental results demonstrate that our methods are effective and efficient in querying the attributed communities on bipartite graphs.
翻译:对双部分图形的社区搜索最近引起了很大的兴趣。 在很多应用中,比如电子商务中的用户-项目双部分图、电影评级网站中的客户-电影双部分图等用户-项目双部分图中,节点往往具有属性,而以前对双部分图形的社区搜索算法忽略了属性,这使得返回的结果在节点属性方面不那么一致。在本文中,我们研究了对双部分图表的归属社区搜索问题。在查询的顶点 q 中,我们的目标是找到一个归宿$left(alpha,\beta\right)$-comunity $G$($G$),其中社区的结构凝聚力被一个 $\left(alpha,\beta\right) $- 核心模型描述,而先前的两组节点的属性与它们的节点属性相似。为了从双部分图表中检索被归属的社区,我们首先提出一个基本算法,由两个步骤组成: 候选人关键词组的生成和核查,然后提出两个改进的查询算法公司和Dec。 Inc建议考虑一个反-lection resual exal exal ex ex ex resual ex resulation roup ex des the we des the des the des des des the des the des des the des the exupolviolviolviolviolviolviolviolviolviolve ex ex</s>