Comparative Explanations of Recommendations
Aobo Yang, Nan Wang, Renqin Cai, Hongbo Deng, Hongning Wang
Abstract
As recommendation is essentially a comparative (or ranking) process, a good explanation should illustrate to users why an item is believed to be better than another, i.e., comparative explanations about the recommended items. Ideally, after reading the explanations, a user should reach the same ranking of items as the system’s. Unfortunately, little research attention has yet been paid on such comparative explanations.
Topics & Concepts
Computer scienceRecommender Systems and TechniquesTopic ModelingMachine Learning in Healthcare