Network Structure Inference, A Survey: Motivations, Methods, and Applications
Ivan Brugere, Brian Gallagher, Tanya Y. Berger-Wolf

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…
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Taxonomy
TopicsComplex Network Analysis Techniques · Opinion Dynamics and Social Influence · Bioinformatics and Genomic Networks
