Abstract. Self-Organizing Maps (SOM) is a powerful tool for clustering and discovering patterns in data. Competitive learning in the SOM training process focusses on finding a neu...
Self-Organizing Maps (SOMs) have been used to visualize tradeoffs of Pareto solutions in the objective function space for engineering design obtained by Evolutionary Computation. F...
This paper proposes a clustering method SOMAK, which is composed by Self-Organizing Maps (SOM) followed by the Ant K-means (AK) algorithm. The aim of this method is not to find an...
Jefferson R. Souza, Teresa Bernarda Ludermir, Lean...
When dense matrix computations are too large to fit in cache, previous research proposes tiling to reduce or eliminate capacity misses. This paper presents a new algorithm for ch...
Recent research in reading comprehension supports the hypothesis that readers are aided by textual cohesion. Traditional readability formulas are not able to effectively assess le...
Erin J. Lightman, Philip M. McCarthy, David F. Duf...