Set Contribution Functions for Quantitative Bipolar Argumentation and their Principles
This work provides incremental theoretical extensions for researchers in computational argumentation, with potential applications in recommendation systems.
The authors tackled the problem of quantifying the contribution of sets of arguments to a topic in quantitative bipolar argumentation graphs, generalizing existing single-argument functions and analyzing them with new principles focused on argument interactions.
We present functions that quantify the contribution of a set of arguments in quantitative bipolar argumentation graphs to (the final strength of) an argument of interest, a so-called topic. Our set contribution functions are generalizations of existing functions that quantify the contribution of a single contributing argument to a topic. Accordingly, we generalize existing contribution function principles for set contribution functions and provide a corresponding principle-based analysis. We introduce new principles specific to set-based functions that focus on properties pertaining to the interaction of arguments within a set. Finally, we sketch how the principles play out across different set contribution functions given a recommendation system application scenario.