Year

1996

Degree Name

Master of Science

Department

Computer Science Department

Abstract

A neural network approach to low-level user modelling is described, in the context of text editing tasks using the Jove editor. Knowledge of a user's expertise is extracted automatically, based on their interaction with Jove over a two-week period. A multi-layered perceptron (MLP) classifier which uses rprop, or resilient backpropagation" learning and incorporate input data fuzzification is developed to classify users into one of five expertise levels. Classification into correct level is achieved in around 80% of cases, with misclassification being restricted to adjacent classes. The neuro-flizzy system is seen to outperform not only the binary classifier of Beale (1989), but also production rule and inductive expert systems developed especially for comparison purposes in this study.

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