The task of identifying redundant information in documents that are generated from multiple sources provides a significant challenge for summarization and QA systems. Traditional ...
We developed a model based on nonparametric Bayesian modeling for automatic discovery of semantic relationships between words taken from a corpus. It is aimed at discovering seman...
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
In recent years the complexity of numerical computations in computational financial applications has been increased enormously. Monte Carlo algorithm is one of main tools in comput...
Projective Clustering Ensembles (PCE) are a very recent advance in data clustering research which combines the two powerful tools of clustering ensembles and projective clustering...
Francesco Gullo, Carlotta Domeniconi, Andrea Tagar...