A Survey on Link prediction

Zenodo (CERN European Organization for Nuclear Research) 2026 Preprint Open access

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Authors: Nishad S, Srikesh Namboodiri C.M, Dr Jayakumar P
DOI: 10.5281/zenodo.18214886
Cited by: 0

Abstract

This paper surveys the field of link prediction, focusing on the evolution of algorithms, theirmethodologies, and diverse application domains. We provide a structured review of classicalheuristic approaches, machine learning, and deep learning techniques, and discuss how the selection of methods depends on the network’s domain and structure.The work emphasizes domainaware method selection and highlights common evaluation pitfalls affecting reproducibility

Fields of Study & Subjects

Complex Network Analysis Techniques Advanced Graph Neural Networks Recommender Systems and Techniques

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
11 January 2026
Language
EN
Document type
Preprint