We investigate the novel problem of event recognition from news webpages. "Events" are basic text units containing news elements. We observe that a news article is always...
We propose a unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including: part-of-speech tagging, chunki...
We present a transformation scheme that mediates between description logics (DL) or RDF-encoded ontologies and type hierarchies in feature logics (FL). The DL-to-FL direction is i...
In this article we want to demonstrate that annotation of multiword expressions in the Prague Dependency Treebank is a well defined task, that it is useful as well as feasible, an...
Gradient boosting is a flexible machine learning technique that produces accurate predictions by combining many weak learners. In this work, we investigate its use in two applica...
Bin Zhang, Abhinav Sethy, Tara N. Sainath, Bhuvana...