ABSTRACT

This study explores the design and application of natural language text-based processing systems, based on generative linguistics, empirical copus analysis, and artificial neural networks. It emphasizes the practical tools to accommodate the selected system.

Symbolic approaches to natural language processing; tokenisation and sentence segmentation; lexical analysis; parsing techniques; semantic analysis; discourse structure and intention recognition; natural language generation; intelligent writing assistance database interfaces; information extraction; the generation of reports from databases; the generation of multimedia presentations; machine translation; dialogue systems - from theory to practice in TRAINS-96 empirical approaches to natural language processing; corpus creation for data-intensive linguistics; part-of-speech tagging; alignment; contextual word similarity; computing similarity; collocations; statistical parsing; authorship identificaiton and computational stylometry; lexical knowledge acquisition; example-based machine translation; word-sense disambiguation; NLP based on artificial neural-networks - introduction.