An explanation-based approach to improve retrieval in case-based planning
New directions in AI planning
Fast discovery of association rules
Advances in knowledge discovery and data mining
The FindMe Approach to Assisted Browsing
IEEE Expert: Intelligent Systems and Their Applications
Explanation-Driven Case-Based Reasoning
EWCBR '93 Selected papers from the First European Workshop on Topics in Case-Based Reasoning
Compound Critiques for Conversational Recommender Systems
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
Explanation in Case-Based Reasoning---Perspectives and Goals
Artificial Intelligence Review
The Explanatory Power of Symbolic Similarity in Case-Based Reasoning
Artificial Intelligence Review
A Case-Based Explanation System for Black-Box Systems
Artificial Intelligence Review
Explanation in Recommender Systems
Artificial Intelligence Review
An evaluation of the usefulness of case-based explanation
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
Knowledge-based navigation of complex information spaces
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Explanation in Case-Based Reasoning---Perspectives and Goals
Artificial Intelligence Review
Explanation in Recommender Systems
Artificial Intelligence Review
Preference-Based Organization Interfaces: Aiding User Critiques in Recommender Systems
UM '07 Proceedings of the 11th international conference on User Modeling
Interaction design guidelines on critiquing-based recommender systems
User Modeling and User-Adapted Interaction
Mixed collaborative and content-based filtering with user-contributed semantic features
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
The adaptive web
The fun begins with retrieval: explanation and CBR
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
Evaluating CBR systems using different data sources: a case study
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
Ontology-driven development of conversational CBR systems
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
Critiquing-based recommenders: survey and emerging trends
User Modeling and User-Adapted Interaction
ReComment: towards critiquing-based recommendation with speech interaction
Proceedings of the 7th ACM conference on Recommender systems
| Hi-index | 0.00 |
When it comes to buying expensive goods people expect to be skillfully steered through the options by well-informed sales assistants who are capable of balancing the user's many and varied requirements. In addition users often need to be educated about the product space, especially if they are to come to understand what is available and why certain options are being recommended by the sales-assistant. It is now well accepted that interactive recommender systems, the on-line equivalent of a sales assistant, also need to educate users about the product space and to justify their recommendations. In this paper we focus on a novel approach to explanation. Instead of attempting to justify a particular recommendation we focus on how certain types of feedback can help users to understand the recommendation opportunities that remain if the current recommendation should not meet their requirements. Specifically, we describe how this approach to explanation is tightly coupled with the generation of compound critiques, which act as a form of feedback for users. Furthermore, we argue that these explanation-rich critiques have the potential to dramatically improve recommender performance and usability.