关键词: 多维分析, 图, 基于链接的度量

Abstract: Graph data are ubiquitous. There exist different kinds of relationships between any two nodes. Different relationships can be modeled by different graphs, different graphs reflect different kinds of relationships between individuals. From different perspectives, the structure of the same network is different, where perspective denotes relationship or union of relationship. On the other hand, the operators in the graph such as link-based measure, reachability query, rely on the structure of the graph. Therefore, this paper proposes the framework of multidimensional analysis on graph data, and uses a case study of perspective-aware link-based top-k query to verify the effectiveness of the framework. Firstly, this paper proposes importance biased random walk on multigraph. Then, this paper presents the corresponding upper/lower bounds, where the bounds are used to accelerate the query speed. At last, this paper validates the effectiveness of the framework by performing extensive experiments, and discusses future works.

Key words:  multidimensional analysis, graph, link-based measure