This paper presents a cluster-based text categorization system which uses class distributional clustering of words. We propose a new clustering model which considers the global in...
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
In recent years realistic input models for geometric algorithms have been studied. The most important models introduced are fatness, low density, unclutteredness, and small simple...
Mark de Berg, Haggai David, Matthew J. Katz, Mark ...
We give an algorithm that with high probability properly learns random monotone DNF with t(n) terms of length log t(n) under the uniform distribution on the Boolean cube {0, 1}n ....
Jeffrey C. Jackson, Homin K. Lee, Rocco A. Servedi...
This paper presents a unified utility framework for resource selection of distributed text information retrieval. This new framework shows an efficient and effective way to infer ...