Work

A Sublinear Algorithm for Approximate Shortest Paths in Large Networks

Year: 2025

Type: conference-paper

Abstract: Computing distances and finding shortest paths in massive real-world networks is a fundamental algorithmic task in network analysis. There are two main approaches to solving this task. On one end are traversal-based algorithms like bidirectional breadth-first search (BiBFS), which have no preprocessing step but are slow on individual distance inquiries. On the other end are indexing-based approaches, which create and maintain a large index. This allows for answering individual inquiries very fast; however, index creation is prohibitively expensive. We seek to bridge these two extremes: quickly answer distance inquiries without the need for costly preprocessing.

DOI: 10.1145/3701551.3703512

Authors: Sabyasachi Basu, Nadia Kōshima, Talya Eden, Omri Ben-Eliezer, C. Seshadhri

Institutions: University of California, Santa Cruz, Massachusetts Institute of Technology, Bar-Ilan University, Technion – Israel Institute of Technology

Language: English

Topic: Graph Theory and Algorithms

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Funder: Universitas Brawijaya

Award: G8961025289