exampleRankXALExplain
exampleRankXALExplain is a modular explainability component designed to accompany ranking models within the exampleRank framework. It provides interpretable explanations for why specific items are ranked at certain positions and how alternative features would affect rankings. The goal is to increase transparency, enable auditing, and support user trust in automated ranking decisions.
The component consists of an explanation generator, a feature attribution engine, a user-facing narrative layer, and
Methodologically, it supports multiple explanation modalities. Feature attributions quantify the contribution of individual features to a
Applications include e-commerce search and recommendation systems, document or content ranking, and candidate sorting in talent
See also: explainable AI, SHAP, LIME, ranking explainability, model transparency.