We describe a generative probabilistic model of natural language, which we call HBG, that takes advantage of detailed linguistic information to resolve ambiguity. HBG incorporates...
Ezra Black, Frederick Jelinek, John D. Lafferty, D...
Abstract. Recommender systems face up to current information overload by selecting automatically items that match the personal preferences of each user. The so-called content-based...
Abstract Resource adaptlvity" Because the sets of strucNatural language parsing is conceived to be a procedure of disambiguation, which successively reduces an initially total...
Abstract. Preferences and uncertainty occur in many real-life problems. The theory of possibility is one non-probabilistic way of dealing with uncertainty, which allows for easy in...
Maria Silvia Pini, Francesca Rossi, Kristen Brent ...
We propose two general and robust methods for enriching resources annotated in the Frame Semantic paradigm with syntactic dependency graphs, which can provide useful additional in...