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arXiv · 1901.04873

Multi-Community Detection in Signed Graphs Using Quantum Hardware

Ehsan Zahedinejad·Daniel Crawford·Clemens Adolphs·Jaspreet S. Oberoi
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Abstract

Signed graphs serve as a primary tool for modelling social networks. They can represent relationships between individuals (i.e., nodes) with the use of signed edges. Finding communities in a signed graph is of great importance in many areas, for example, targeted advertisement. We propose an algorithm to detect multiple communities in a signed graph. Our method reduces the multi-community detection problem to a quadratic binary unconstrained optimization problem and uses state-of-the-art quantum or classical optimizers to find an optimal assignment of each individual to a specific community.

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Ehsan Zahedinejad, Daniel Crawford, Clemens Adolphs, Jaspreet S. Oberoi. 2019-01-12. Multi-Community Detection in Signed Graphs Using Quantum Hardware. https://arxiv.org/abs/1901.04873

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