We propose a novel type of document classification task that quantifies how much a given document (review) appreciates the target object using not binary polarity (good or bad) b...
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Learning texts contain much implicit knowledge which is ideally presented to the learner in a structured manner - a typical example being definitions of terms in the text, which w...
LETOR is a benchmark collection for the research on learning to rank for information retrieval, released by Microsoft Research Asia. In this paper, we describe the details of the L...
This paper describes an initial prototype demonstrator of a Companion, designed as a platform for novel approaches to the following: 1) The use of Information Extraction (IE) tech...
Yorick Wilks, Roberta Catizone, Alexiei Dingli, We...