An Axiomatic Study of a Modular Evaluation of Enthymeme Decoding in Weighted Structured Argumentation

An argument can be seen as a pair of premises and a claim they support.

Human arguments are often approximate, with some premises left implicit, leading to an implicit inference of the claim, i.e., forming enthymemes.

To better understand and use them, we must decode these approximate enthymemes, typically by identifying missing premises to make the inference explicit, and, as we propose, by also removing irrelevant content to improve argument quality in specific contexts.

Often, multiple decodings of an enthymeme are possible.

However, no formal method has yet been proposed for identifying higher-quality decodings.

To pave the way, we introduce six types of criteria for evaluating aspects of decodings.

Then, we introduce the concept of a criterion measure, designed to evaluate decodings based on a specific criterion.

In parallel, we define desirable properties for criterion measures, referred to as axioms, and we systematically evaluate our criterion measures with respect to them.

Finally, we introduce the notion of quality measure that combine specific criterion measures to give an overall evaluation of the quality of decodings.