The present work is dedicated to the study of modes of data-presentation in the range between text and informant within the framework of inductive inference. In this study, the le...
Computational models of meaning trained on naturally occurring text successfully model human performance on tasks involving simple similarity measures, but they characterize meani...
Marco Baroni, Brian Murphy, Eduard Barbu, Massimo ...
This paper proposes new extensions of the digital book concept together with the required approaches to support their automatic generation. Most best-sellers have often inspired o...
The IDAS natural-language generation system uses a KL-ONE type classifier to perform content determination, surface realisation, and part of text planning. Generation-by-classific...
People cannot type as fast as they think, especially when faced with the constraints of mobile devices. There have been numerous approaches to solving this problem, including rese...