Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operat...
We describe a machine learning approach for predicting sponsored search ad relevance. Our baseline model incorporates basic features of text overlap and we then extend the model t...
Dustin Hillard, Stefan Schroedl, Eren Manavoglu, H...
This paper describes a framework for defining domain specific Feature Functions in a user friendly form to be used in a Maximum Entropy Markov Model (MEMM) for the Named Entity Re...
Given the interactive media characteristics and intrinsically motivating appeal, computer games are often praised for their potential and value in education. However, comprehensiv...
Abstract. We promote the use of explicit medical knowledge to solve retrieval of information both visual and textual. For text, this knowledge is a set of concepts from a Meta-thes...