In Mathematical, Computer, And Physical Sciences

This thesis presents a new theory of information modelling in natural language process-ing that attempts to resolve anaphoric references, while also addressing the problem of knowledge complexity. A modular model of semantic representation is introduced that addresses the deficiencies of existing representations, as well as the drawbacks associated with expanding these semantic representations. Rather than using a single semantic rep-resentation to model human knowledge and the knowledge within a sentence, the theory proposes a modular, multi-level model which is based around a semantic network. The behaviour of the model uses theories on the nature of working and long-term memory from cognitive psychology. Two methods of artificial neuron activation and decay were implemented – the ACT-R model and the Thompson model. Maximum success rates of 54.10 % and 83.61 % were achieved for The Three Brothers corpus, and maximum success rates of 56.00 % and 86.67 % were achieved for the Rumpelstiltskin corpus. ii This thesis is approve