4 citations · 11 across the 6 of their papers we have counts for
7 papers
Graph3S: A Simple, Speedy and Scalable Distributed Graph Processing System
Xubo Wang, Lu Qin, Lijun Chang +3
Graph is a ubiquitous structure in many domains. The rapidly increasing data volume calls for efficient and scalable graph data processing. In recent years, designing distributed g…
An Optimal and Progressive Approach to Online Search of Top-k Influential Communities
Fei Bi, Lijun Chang, Xuemin Lin +1
Community search over large graphs is a fundamental problem in graph analysis. Recent studies propose to compute top-k influential communities, where each reported community not on…
A Near-optimal Algorithm for Edge Connectivity-based Hierarchical Graph Decomposition
Lijun Chang
Driven by many applications in graph analytics, the problem of computing -edge connected components (-ECCs) of a graph for a user-given has been extensively studied r…
Efficient Graph Edit Distance Computation and Verification via Anchor-aware Lower Bound Estimation
Lijun Chang, Xing Feng, Xuemin Lin +2
Graph edit distance (GED) is an important similarity measure adopted in a similarity-based analysis between two graphs, and computing GED is a primitive operator in graph database…
Enumerating k-Vertex Connected Components in Large Graphs
Dong Wen, Lu Qin, Xuemin Lin +2
Cohesive subgraph detection is an important graph problem that is widely applied in many application domains, such as social community detection, network visualization, and network…
Diversifying Top-K Results
Lu Qin, Jeffrey Xu Yu, Lijun Chang
Top-k query processing finds a list of k results that have largest scores w.r.t the user given query, with the assumption that all the k results are independent to each other. In p…