Network Structure Inference, A Survey: Motivations, Methods, and Applications

TL;DR

This survey reviews methods for inferring network structures from data across various domains, highlighting construction techniques, application-specific questions, and validation strategies for assessing inferred networks.

Contribution

It provides a comprehensive overview of network inference methods, emphasizing the need for standardized validation approaches across different application areas.

Findings

Various methods exist for network inference across domains

Standardized validation strategies are underdeveloped

Network inference techniques are tailored to specific applications

Abstract

Networks represent relationships between entities in many complex systems, spanning from online social interactions to biological cell development and brain connectivity. In many cases, relationships between entities are unambiguously known: are two users 'friends' in a social network? Do two researchers collaborate on a published paper? Do two road segments in a transportation system intersect? These are directly observable in the system in question. In most cases, relationship between nodes are not directly observable and must be inferred: does one gene regulate the expression of another? Do two animals who physically co-locate have a social bond? Who infected whom in a disease outbreak in a population? Existing approaches for inferring networks from data are found across many application domains and use specialized knowledge to infer and measure the quality of inferred network for a specific task or hypothesis. However, current research lacks a rigorous methodology which employs standard statistical validation on inferred models. In this survey, we examine (1) how network representations are constructed from underlying data, (2) the variety of questions and tasks on these representations over several domains, and (3) validation strategies for measuring the inferred network's capability of answering questions on the system of interest.