Explaining collaborative filtering recommendations
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
The role of transparency in recommender systems
CHI '02 Extended Abstracts on Human Factors in Computing Systems
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Improving recommendation lists through topic diversification
WWW '05 Proceedings of the 14th international conference on World Wide Web
An empirical study of the influence of argument conciseness on argument effectiveness
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project (The Addison-Wesley series in artificial intelligence)
Explanation in Recommender Systems
Artificial Intelligence Review
Being accurate is not enough: how accuracy metrics have hurt recommender systems
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Effective explanations of recommendations: user-centered design
Proceedings of the 2007 ACM conference on Recommender systems
A Survey of Explanations in Recommender Systems
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
The Effectiveness of Personalized Movie Explanations: An Experiment Using Commercial Meta-data
AH '08 Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Tagsplanations: explaining recommendations using tags
Proceedings of the 14th international conference on Intelligent user interfaces
Intelligent tagging interfaces: beyond folksonomy
UIST '10 Adjunct proceedings of the 23nd annual ACM symposium on User interface software and technology
d.tour: style-based exploration of design example galleries
Proceedings of the 24th annual ACM symposium on User interface software and technology
Persuasive conversational agent with persuasion tactics
PERSUASIVE'10 Proceedings of the 5th international conference on Persuasive Technology
Collaborative Filtering Recommender Systems
Foundations and Trends in Human-Computer Interaction
ACM Transactions on Interactive Intelligent Systems (TiiS)
The influence of knowledgeable explanations on users' perception of a recommender system
Proceedings of the sixth ACM conference on Recommender systems
Being confident about the quality of the predictions in recommender systems
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Tagcloud-based explanation with feedback for recommender systems
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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This thesis focuses on explanations of recommendations. Explanations can have many advantages, from inspiring user trust to helping users make good decisions. We have identified seven different aims of explanations, and in this thesis we will consider how explanations can be optimized for some of these aims. We will consider both an explanation's content and its presentation. As a domain, we are currently investigating explanations for a movie recommender, and developing a prototype system. This paper summarizes the goals of the thesis, the methodology we are using, the work done so far and our intended future work.