The best attachment consists in finding a good strategy that allows a node inside a network to achieve a high rank. This is an open issue due to its intrinsic computational complexity and to the giant dimension of the involved networks. The ranking of a node has an important impact both in economics and structural term e.g., a higher rank could leverage the number of contacts or the trusting of the node. This paper presents a heuristics aiming at finding a good solution whose complexity is Nlog N. The results show that better rank improvement comes by acquiring long distance in-links whilst human intuition would suggest to select neighbours. The paper discusses the algorithm and simulation on random and scale-free networks.
Titolo: | Climbing Ranking Position via Long-Distance Backlinks |
Autori interni: | |
Data di pubblicazione: | 2018 |
Serie: | |
Handle: | http://hdl.handle.net/20.500.11769/361759 |
ISBN: | 9783030027377 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |