Results 41 to 50 of about 9,577,753 (319)

Predicting the Future Popularity of Academic Publications Using Deep Learning by Considering It as Temporal Citation Networks

IEEE Access, 2023
One of the key goals of Informetrics is to identify citation-based popular articles among so many other aspects, such as determining popular research topics, identifying influential scholars, and predicting hot trends in science. These can be achieved by
Khushnood Abbas, Mohammad Kamrul Hasan, Alireza Abbasi, Umi Asma Mokhtar, Asif Khan, Siti Norul Huda Sheikh Abdullah, Shi Dong, Shayla Islam, Dabiah Alboaneen, Fatima Rayan Awad Ahmed   +9 more
doaj   +1 more source

Temporal network embedding framework with causal anonymous walks representations [PDF]

PeerJ Computer Science, 2022
Many tasks in graph machine learning, such as link prediction and node classification, are typically solved using representation learning. Each node or edge in the network is encoded via an embedding.
Ilya Makarov, Andrey Savchenko, Arseny Korovko, Leonid Sherstyuk, Nikita Severin, Dmitrii Kiselev, Aleksandr Mikheev, Dmitrii Babaev   +7 more
doaj   +2 more sources

Temporal-Kernel Recurrent Neural Networks [PDF]

Neural Networks, 2010
A Recurrent Neural Network (RNN) is a powerful connectionist model that can be applied to many challenging sequential problems, including problems that naturally arise in language and speech. However, RNNs are extremely hard to train on problems that have long-term dependencies, where it is necessary to remember events for many timesteps before using ...
Sutskever, Ilya, Hinton, Geoffrey
openaire   +2 more sources

A theory of pattern formation for reaction–diffusion systems on temporal networks

Proceedings of the Royal Society A, 2021
Networks have become ubiquitous in the modern scientific literature, with recent work directed at understanding ‘temporal networks’—those networks having structure or topology which evolves over time. One area of active interest is pattern formation from
R. V. Van Gorder
semanticscholar   +1 more source

Foundations and Modeling of Dynamic Networks Using Dynamic Graph Neural Networks: A Survey

IEEE Access, 2021
Dynamic networks are used in a wide range of fields, including social network analysis, recommender systems and epidemiology. Representing complex networks as structures changing over time allow network models to leverage not only structural but also ...
Joakim Skarding, Bogdan Gabrys, Katarzyna Musial   +2 more
doaj   +1 more source

Graph Metrics for Temporal Networks [PDF]

, 2013
Temporal networks, i.e., networks in which the interactions among a set of elementary units change over time, can be modelled in terms of time-varying graphs, which are time-ordered sequences of graphs over a set of nodes. In such graphs, the concepts of
A Arenas, A Broder, A Clauset, A Gautreau, A Vazquez, A.-L. Barabasi, D Kempe, DJ Watts, E Bullmore, EA Leicht, F Vico Fallani De, G Miritello, J Stehlé, J Tang, J Tang, J Tang, M Karsai, M Newman, M Valencia, M.E.J. Newman, M.E.J. Newman, M.E.J. Newman, M.E.J. Newman, M.E.J. Newman, M.E.J. Newman, P Grindrod, P Holme, PJ Mucha, R Albert, R Albert, R Milo, R Milo, RK Pan, RM Karp, S Boccaletti, S Fortunato, S Scellato, V Kostakos, V Latora, V Nicosia   +39 more
core   +3 more sources

Dynamic Community Discovery Method Based on Phylogenetic Planted Partition in Temporal Networks

Applied Sciences, 2022
As most of the community discovery methods are researched by static thought, some community discovery algorithms cannot represent the whole dynamic network change process efficiently.
Xiaoyang Liu, Nan Ding, Giacomo Fiumara, Pasquale De Meo, Annamaria Ficara   +4 more
doaj   +1 more source

Mining Stable Quasi-Cliques on Temporal Networks

IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021
Real-world networks, such as phone-call networks and social networks, are often not static but temporal. Mining cohesive subgraphs from static graphs is a fundamental task in network analysis and has been widely investigated in the past decades. However,
Longlong Lin, Pingpeng Yuan, Ronghua Li, Jifei Wang, Ling Liu, Hai-rong Jin   +5 more
semanticscholar   +1 more source

Brief Announcement: Integrating Temporal Information to Spatial Information in a Neural Circuit [PDF]

, 2019
In this paper, we consider networks of deterministic spiking neurons, firing synchronously at discrete times. We consider the problem of translating temporal information into spatial information in such networks, an important task that is carried out by ...
Lynch, Nancy, Wang, Mien Brabeeba
core   +1 more source

Access Controlled Temporal Networks

Proceedings of the 9th International Conference on Agents and Artificial Intelligence, 2017
We define Access-Controlled Temporal Networks (ACTNs) as an extension of Conditional Simple Temporal Networks with Uncertainty (CSTNUs). CSTNUs are able to handle features such as contingent durations and conditional constraints, and have thus been used to model the temporal constraints of workflows underlying business processes.
COMBI, Carlo, POSENATO, Roberto, VIGANO', Luca, Zavatteri, Matteo   +3 more
openaire   +5 more sources