In a higher level task such as clustering of web results or word sense disambiguation, knowledge of all possible distinct concepts in which an ambiguous word can be expressed woul...
We use clustering to derive new relations which augment database schema used in automatic generation of predictive features in statistical relational learning. Clustering improves...
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Analyzing sequence data has become increasingly important recently in the area of biological sequences, text documents, web access logs, etc. In this paper, we investigate the pro...
In this paper we propose a new information-theoretic divisive algorithm for word clustering applied to text classification. In previous work, such "distributional clustering&...
Inderjit S. Dhillon, Subramanyam Mallela, Rahul Ku...