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...
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Existing research on news video analysis mainly concentrates on structure analysis, semantic concept detection, annotation and search. However, little work has been contributed to...
We describe work on automatically assigning labels to books using user-defined tags as the label set. Using supervised learning and exploring both binary and multiclass classifica...
In traditional text classification, a classifier is built using labeled training documents of every class. This paper studies a different problem. Given a set P of documents of a ...