Efficient processing of k-hop reachability queries on temporal bipartite graphs

Given a temporal bipartite graph, the $k$-hop reachability query is used to determine whether there exists a path between two vertices in the graph that satisfies both time and length constraints. The $k$-hop reachability queries on temporal bipartite graphs can be used in various scenarios to facilitate data analysis, such as epidemic prevention and control and information dissemination, etc. For $k$-hop reachability queries processing on temporal bipartite graphs, existing methods suffer from two problems: (1) false-negative problem, which means that for some reachable queries, existing approaches return unreachable results; (2) lack of support for length constraint. To tackle the above problems, we first analyze the essential reasons of false-negative problem, and propose a traversal-based strategy to avoid the false-negative problem. To improve the efficiency, we propose a graph transform based approach to reduce the cost of graph traversal operation. We then propose to construct a compact index based on the transformed graph, which covers both time and length constraints of all vertex pairs, such that to avoid the expensive graph traversal operation. We further propose efficient algorithms to update the index when the temporal bipartite graph changes. Finally, we conduct rich experiments on real-world datasets. The experimental results show that, our methods completely avoid false-negative problem, and the query efficiency of our index-based method is more than three orders of magnitude faster than the online approach.