1 citations · 1 across the 5 of their papers we have counts for
5 papers
Rough Sets for Explainability of Spectral Graph Clustering
Bartłomiej Starosta, Sławomir T. Wierzchoń, 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
Mieczysław A. Kłopotek, Sławomir T. Wierzchoń, Bartłomiej 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
Mieczysław A. Kłopotek, Sławomir T. Wierzchoń, Bartłomiej 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…
Eigenvalue-based Incremental Spectral Clustering
Mieczysław A. Kłopotek, Bartłmiej Starosta, Sławomir T. Wierzchoń
Our previous experiments demonstrated that subsets collections of (short) documents (with several hundred entries) share a common normalized in some way eigenvalue spectrum of comb…
Explainable Graph Spectral Clustering of Text Documents
Bartłomiej Starosta, Mieczysław A. Kłopotek, Sławomir T. Wierzchoń
Spectral clustering methods are known for their ability to represent clusters of diverse shapes, densities etc. However, results of such algorithms, when applied e.g. to text docum…