We present a discriminative method for learning selectional preferences from unlabeled text. Positive examples are taken from observed predicate-argument pairs, while negatives ar...
We call data weakly labeled if it has no exact label but rather a numerical indication of correctness of the label "guessed" by the learning algorithm - a situation comm...
Author identification models fall into two major categories according to the way they handle the training texts: profile-based models produce one representation per author while in...
In this paper, we give an overview of a system (CAIMAN) that can facilitate the exchange of relevant documents between geographically dispersed people in Communities of Interest. ...
We present two instantiations of generic Interactive State Machines (ISMs) with mobility features which are useful for modeling and verifying dynamically changing mobile systems. I...