Randomised techniques allow very big language models to be represented succinctly. However, being batch-based they are unsuitable for modelling an unbounded stream of language whi...
In this paper we propose a novel statistical language model to capture long-range semantic dependencies. Specifically, we apply the concept of semantic composition to the problem ...
The recent availability of large corpora for training N-gram language models has shown the utility of models of higher order than just trigrams. In this paper, we investigate meth...
In this paper we present a framework for the evaluation and (re)design of modeling languages. We focus here on the evaluation of the suitability of a language to model a set or rea...
This paper presents a specifically database-inspired approach (called DOGMA) for engineering formal ontologies, implemented as shared resources used to express agreed formal semant...