We describe a set of supervised machine learning experiments centering on the construction of statistical models of WH-questions. These models, which are built from shallow lingui...
On the Semantic Web, decision makers (humans or software agents alike) are faced with the challenge of examining large volumes of information originating from heterogeneous sources...
This paper explores a topological perspective of planning in the presence of uncertainty, focusing on tasks specified by goal states in discrete spaces. The paper introduces stra...
The design of algorithms that can run unchanged yet efficiently on a variety of machines characterized by different degrees of parallelism and communication capabilities is a hig...
Gianfranco Bilardi, Andrea Pietracaprina, Geppino ...
In many classification tasks training data have missing feature values that can be acquired at a cost. For building accurate predictive models, acquiring all missing values is of...
Prem Melville, Foster J. Provost, Raymond J. Moone...