The thesis describes the application of the relaxation labelling algorithm to NLP
disambiguation. Language is modelled through context constraint inspired on Constraint …

In this paper, we present a novel technique to learn a tree-like structure for a content planner
from an aligned corpus of semantic inputs and corresponding, humanproduced, outputs. We …

Automatic summarization is emerging as a feasible instrument to help biomedical
researchers to access online literature and face information overload. The Natural …

This paper describes an evolutionary approach to the problem of inferring stochastic context-
free grammars from finite language samples. The approach employs a distributed, steady …

Natural language processing grapples with an ever-changing and moving target. The focus
of study, natural language, is natural because it changes, interacts and evolves in various …

In many applications, it is useful to extract structured data from sections of unstructured text.
A common approach is to use pattern matching (eg, regular expressions) or more general …

Autotuning is an empirical optimization approach in which the configuration space of an
algorithmic code is explored in a systematic manner for a variety of software and hardware …

Speech and language processing systems can be categorised according to whether they
make use of predefined linguistic information and rules or are data driven and therefore …

In this paper, an agent-based evolutionary computing technique is introduced, that is geared
towards the automatic induction and optimization of grammars for natural language …

Abstract Grammar-based Classifier System (GCS) is a new version of Learning Classifier
Systems in which classifiers are represented by context-free grammar in Chomsky Normal …