A cognitively-based neural network for determining paragraph coherence

The authors report on an effort in artificial neural network (ANN) technology to use content-independent elements of prose as predictors of paragraph logic structures. They intend to embed the trained network in an intelligent tutor to teach writing skills. An attempt is made to find patterns in the nonambiguous lexical and syntactic features if discourse that predict the semantic/cognitive level of interpretation. An NN implementation of the modified Christensen method is considered. It is noted that ANN technology's ability to deal with fuzzy logic, feature extraction, classification, and predictive modeling makes a neural network the best choice for the present application.<<ETX>>