Explaining collaborative filtering recommendations
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Content-boosted collaborative filtering for improved recommendations
Eighteenth national conference on Artificial intelligence
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
IEEE Transactions on Knowledge and Data Engineering
A maximum entropy web recommendation system: combining collaborative and content features
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
CinemaScreen Recommender Agent: Combining Collaborative and Content-Based Filtering
IEEE Intelligent Systems
Modeling relationships at multiple scales to improve accuracy of large recommender systems
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Gradual trust and distrust in recommender systems
Fuzzy Sets and Systems
A Survey of Explanations in Recommender Systems
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
Collaborative filtering with ordinal scale-based implicit ratings for mobile music recommendations
Information Sciences: an International Journal
Information Sciences: an International Journal
A web based consensus support system for group decision making problems and incomplete preferences
Information Sciences: an International Journal
User comments for news recommendation in forum-based social media
Information Sciences: an International Journal
Collaborative filtering based on significances
Information Sciences: an International Journal
A generalized taxonomy of explanations styles for traditional and social recommender systems
Data Mining and Knowledge Discovery
Providing Justifications in Recommender Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Incorporating reliability measurements into the predictions of a recommender system
Information Sciences: an International Journal
Knowledge-Based Systems
Hierarchical graph maps for visualization of collaborative recommender systems
Journal of Information Science
| Hi-index | 0.07 |
In this paper, we present a novel technique for explaining the recommendations made by recommender systems based on collaborative filtering. Our technique is based on the visualisation of trees of items, and it provides users with a quick and attractive way of understanding the recommendations. This type of visualisation provides users with valuable information about the reliability of the recommendations and the importance of the ratings the user has made, which may help users to decide which recommendation to choose.