3 papers
Rough Sets for Explainability of Spectral Graph Clustering
BartÅomiej Starosta, SÅawomir T. WierzchoÅ, Piotr Borkowski +4
Graph Spectral Clustering methods (GSC) allow representing clusters of diverse shapes, densities, etc. However, the results of such algorithms, when applied e.g. to text documents,…
Explainable Graph Spectral Clustering For GloVe-like Text Embeddings
MieczysÅaw A. KÅopotek, SÅawomir T. WierzchoÅ, BartÅomiej Starosta +3
In a previous paper, we proposed an introduction to the explainability of Graph Spectral Clustering results for textual documents, given that document similarity is computed as cos…
A Method for Handling Negative Similarities in Explainable Graph Spectral Clustering of Text Documents -- Extended Version
MieczysÅaw A. KÅopotek, SÅawomir T. WierzchoÅ, BartÅomiej Starosta +2
This paper investigates the problem of Graph Spectral Clustering with negative similarities, resulting from document embeddings different from the traditional Term Vector Space (li…