An Analysis of Local Explanation with LIME-RS
Author(s)
Anelli, Vito Walter
Bellogín, Alejandro
Noia, Tommaso Di
Paparella, Vincenzo
Date Issued
2022
Type
conferenceObject
Volume
3177
Journal
Abstract
Explainable Recommendation has attracted a lot of attention due to a renewed interest in explainable artificial intelligence. In particular, post-hoc approaches have proved to be the most easily applicable ones, since they treat as black boxes the increasingly complex recommendation models. Recent literature has shown that for post-hoc explanations based on local surrogate models, there are problems related to the robustness of the approach itself. This consideration becomes even more relevant in human-related tasks, from transparency or trustworthiness points of view – like recommendation. We show how the behavior of LIME-RS – a classical post-hoc model based on surrogates – is strongly model-dependent and does not prove to be accountable for the explanations generated.
Conference(s)
12th Italian Information Retrieval Workshop, IIR 2022