@inproceedings{b91a3f52dc224572916e1f3c6ca6d43a,
title = "De-evolution of Preferential Attachment Trees",
abstract = "Given a graph Gt which is a result of a t time, evolutionary process, the goal of graph de-evolution of Gt is to infer what was the structure of the graph Gt′ for t′< t. This general inference problem is very important for understanding the mechanisms behind complex systems like social networks and their asymptotic behavior. In this work we take a step in this direction and consider undirected, unlabeled trees that are the result of the well known random preferential attachment process. We compute the most likely root set (possible isomorphic patient zero candidates) of the tree, as well as the most likely previous graph Gt - 1 structure. While the one step forward reasoning in preferential attachment is very simple, the backward (past) reasoning is more complex and includes the use of the automorphism and isomorphism of graphs, which we elucidate here.",
keywords = "De-evolution, Evolution, Preferential attachment, Social networks, Time, Trees",
author = "Chen Avin and Yuri Lotker",
note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 9th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2020 ; Conference date: 01-12-2020 Through 03-12-2020",
year = "2021",
month = jan,
day = "1",
doi = "10.1007/978-3-030-65351-4_41",
language = "English",
isbn = "9783030653507",
series = "Studies in Computational Intelligence",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "508--519",
editor = "Benito, {Rosa M.} and Chantal Cherifi and Hocine Cherifi and Esteban Moro and Rocha, {Luis Mateus} and Marta Sales-Pardo",
booktitle = "Complex Networks and Their Applications IX - Volume 2, Proceedings of the Ninth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2020",
address = "Germany",
}