Drawing large weighted graphs using clustered force-directed algorithm
Clustered graph drawing is widely considered as a good method to overcome the scalability
problem when visualizing large (or huge) graphs. Force-directed algorithm is a popular …
problem when visualizing large (or huge) graphs. Force-directed algorithm is a popular …
GraphViz2Vec: A Structure-aware Feature Generation Model to Improve Classification in GNNs
SK Chatterjee, S Kundu - arXiv preprint arXiv:2401.17178, 2024 - arxiv.org
GNNs are widely used to solve various tasks including node classification and link
prediction. Most of the GNN architectures assume the initial embedding to be random or …
prediction. Most of the GNN architectures assume the initial embedding to be random or …
A fast self-organizing map algorithm by using genetic selection
H Ni - 2009 Third International Symposium on Intelligent …, 2009 - ieeexplore.ieee.org
Self-organizing feature map is able to represent the topological structure of the input data in
a lower dimensional space, but however, at the cost of a huge amount of iterations. This …
a lower dimensional space, but however, at the cost of a huge amount of iterations. This …
Applying hybrid graph drawing and clustering methods on stock investment analysis
M Zreika, ME Varua - International Journal of Economics …, 2016 - publications.waset.org
Stock investment decisions are often made based on current events of the global economy
and the analysis of historical data. Conversely, visual representation could assist investors' …
and the analysis of historical data. Conversely, visual representation could assist investors' …
Applying data visualization methods on Australian stock investment analytics
Stock investment decisions are often made based on current events of the global economy
and the analysis of historical data. Conversely, visual representations may assist investors …
and the analysis of historical data. Conversely, visual representations may assist investors …