Towards a natural language driven automated help desk

Abstract

In this paper, we present the linguistic components required for a natural language driven automated help desk. This work is significant for two reasons: First, the combination of neural networks and supertagging represents a novel and very robust way to classify non-trivial user utterances. Second, we show a novel way of integrating known linguistic techniques for the analysis of user input, knowledge processing, and generation of system responses, resulting in a natural language interface both for input and output. Our approach separates domain specific, language specific and discourse specific knowledge.