Dynamic Critiquing

A technique for automatically generating useful compound critiques over multiple case features is described and it is demonstrated how this can significantly improve the performance of a conversational recommender system.

Abstract

Critiquing is a powerful style of feedback for case-based recommender systems. Instead of providing detailed feature values, users indicate a directional preference for a feature. For example, a user might ask for a 'less expensive' restaurant in a restaurant recommender; 'less expensive' is a critique over the price feature. The value of critiquing is that it is generally applicable over a wide range of domains and it is an effective means of focusing search. To date critiquing approaches have usually been limited to single-feature critiques, and this ultimately limits the degree to which a given critique can eliminate unsuitable cases. In this paper we propose extending the critiquing concept to cater for the possibility of compound critiques – critiques over multiple case features. We describe a technique for automatically generating useful compound critiques and demonstrate how this can significantly improve the performance of a conversational recommender system. We also argue that this generalised form of critiquing offers explanatory benefits by helping the user to better understand the structure of the recommendation space.