Efficiently Answering Quality Constrained Shortest Distance Queries in Large Graphs

Abstract

The shortest-path distance is a fundamental concept in graph data analytics and has been extensively studied in literature. In many real-world applications, quality constraints are naturally associated with edges in the graph, and finding the shortest distance between vertices along only valid edges (i.e., edges that satisfy a given quality constraint) is also critical. In this work, we investigate this novel and important problem of quality constraint shortest distance queries. We propose an efficient index structure based on 2-hop labeling approaches. Supported by a path dominance relationship incorporating both quality and length information, we demonstrate the minimal property of the new index. An efficient query processing algorithm is also developed. Extensive experimental studies over real-life datasets demonstrates efficiency and effectiveness of our techniques