TopCom: Index for Shortest Distance Query in Directed Graph
Vachik S. Dave, Mohammad Al Hasan

TL;DR
TopCom is a new indexing method for exact shortest distance queries in directed graphs, offering superior scalability and faster query response times by leveraging DAG structures, especially in graphs with small SCCs.
Contribution
The paper introduces TopCom, a novel index structure that improves exact shortest distance querying efficiency, outperforming existing methods in scalability and speed.
Findings
TopCom outperforms IS-Label and TreeMap in scalability.
TopCom provides faster query responses for large graphs.
Exploiting DAG structures enhances performance in graphs with small SCCs.
Abstract
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…
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Taxonomy
TopicsData Management and Algorithms · Advanced Database Systems and Queries · Peer-to-Peer Network Technologies
