Towards a Noise-Tolerant, Representation-Independent Mechanism for Argument Interpretation

We describe a mechanism for the interpretation of arguments, which can cope with noisy conditions in terms of wording, beliefs and argument structure. This is achieved through the application of the Minimum Message Length Principle to evaluate candidate interpretations. Our system receives as input a quasi-Natural Language argument, where propositions are presented in English, and generates an interpretation of the argument in the form of a Bayesian network (BN). Performance was evaluated by distorting the system's arguments (generated from a BN) and feeding them to the system for interpretation. In 75% of the cases, the interpretations produced by the system matched precisely or almost-precisely the representation of the original arguments.

• Type: Journal
• Year: 2002
• Where: COLING
• Authors: Ingrid Zukerman, Sarah George
• Keywords: COLING 2002, COLING 2008, Minimum Message Length, Noisy Conditions, Quasi-natural Language Argument