Many existing techniques for term extraction are heuristically-motivated and criticised as ad-hoc. The definitions and assumptions critical to set the boundary for the effective...
In this paper, we consider the problem of community detection in directed networks by using probabilistic models. Most existing probabilistic models for community detection are ei...
Many applications today need to manage large data sets with uncertainties. In this paper we describe the foundations of managing data where the uncertainties are quantified as pro...
Efficient learnability using the state merging algorithm is known for a subclass of probabilistic automata termed µ-distinguishable. In this paper, we prove that state merging alg...
Omri Guttman, S. V. N. Vishwanathan, Robert C. Wil...
Most of the approaches for dealing with uncertainty in the Semantic Web rely on the principle that this uncertainty is already asserted. In this paper, we propose a new approach t...