TopCom：有向图中最短距离查询的索引
TopCom: Index for Shortest Distance Query in Directed Graph
摘要：
图中两点间的最短距离是一个重要的问题，因为它在地理空间数据库、社会网络分析和信息检索等领域有着广泛的应用。经典算法（如Dijkstra）在多项式时间内解决了这个问题，但这些算法不能对大型图上的大量突发查询提供实时响应。因此，基于索引的解决方案，预处理图，以实时有效地回答（准确或近似）大量的距离查询，正变得越来越流行。现有的解决方案在索引大小、索引构建时间、查询时间和准确性方面具有不同的性能。在这项工作中，我们提出了T OP COM，一种新的基于索引的解决方案，准确地回答距离查询。我们的实验与现有的两个国家的最先进的方法（IS-Label和TreeMap）显示的优越性，T OP COM这两种方法，考虑到可扩展性和查询时间。此外，T OP C OM的索引利用了图中的DAG（有向无环图）结构，这使得它在输入图的SCC（强连通分量）相对较小的情况下比现有方法快得多。
英文摘要：
Finding shortest distance between two vertices in a graph is an important problem due to its numerous applications in diverse domains, including geo-spatial databases, social network analysis, and information retrieval. Classical algorithms (such as, Dijkstra) solve this problem in polynomial time, but these algorithms cannot provide real-time response for a large number of bursty queries on a large graph. So, indexing based solutions that pre-process the graph for efficiently answering (exactly or approximately) a large number of distance queries in real-time is becoming increasingly popular. Existing solutions have varying performance in terms of index size, index building time, query time, and accuracy. In this work, we propose T OP C OM , a novel indexing-based solution for exactly answering distance queries. Our experiments with two of the existing state-of-the-art methods (IS-Label and TreeMap) show the superiority of T OP C OM over these two methods considering scalability and query time. Besides, indexing of T OP C OM exploits the DAG (directed acyclic graph) structure in the graph, which makes it significantly faster than the existing methods if the SCCs (strongly connected component) of the input graph are relatively small.
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