Explaining collaborative filtering recommendations
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Exposing profiles to build trust in a recommender
CHI '02 Extended Abstracts on Human Factors in Computing Systems
MyLifeBits: fulfilling the Memex vision
Proceedings of the tenth ACM international conference on Multimedia
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
ComicDiary: Representing Individual Experiences in a Comics Style
UbiComp '02 Proceedings of the 4th international conference on Ubiquitous Computing
Digital memories in an era of ubiquitous computing and abundant storage
Communications of the ACM - Personal information management
The adaptive web: methods and strategies of web personalization
The adaptive web: methods and strategies of web personalization
SharedLife: towards selective sharing of augmented personal memories
Reasoning, Action and Interaction in AI Theories and Systems
Bisociative music discovery and recommendation
Bisociative Knowledge Discovery
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Advances in technological support for augmented personal memories make possible new ways of enhancing the process of product recommendation. Instead of simply analyzing information about a user’s past behavior in order to generate recommendations, a recominder system can additionally supply various types of information from the user’s augmented memory that allows the user to take a more active role in the search for suitable products. We illustrate the paradigm of recomindation with reference to a prototype implementation of the system Specter in a CD shopping scenario and the results of a study with 20 subjects, who found most of the recomindation functionality to constitute a useful enhancement of their shopping experience.