We propose an information-theoretic clustering approach that incorporates a pre-known partition of the data, aiming to identify common clusters that cut across the given partition...
During the last years, a wide range of huge networks has been made available to researchers. The discovery of natural groups, a task called graph clustering, in such datasets is a ...
This paper investigates the applicability of distributed clustering technique, called RACHET [1], to organize large sets of distributed text data. Although the authors of RACHET c...
Broad-coverage lexical resources such as WordNet are extremely useful. However, they often include many rare senses while missing domain-specific senses. We present a clustering a...
We propose a new method, called SimClus, for clustering with lower bound on similarity. Instead of accepting k the number of clusters to find, the alternative similarity-based app...
Mohammad Al Hasan, Saeed Salem, Benjarath Pupacdi,...