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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | O'Donovan, J. Gretarsson, B. Bostandjiev, S. Hollerer, T. Smyth, B. |
| Copyright Year | 2009 |
| Abstract | Collaborative or "Social" filtering has been successfully deployed over the years as a technique for analyzing large amounts of user-preference knowledge to predict interesting items for an individual user. The black-box nature of most collaborative filtering (CF) applications leave the user wondering how the system arrived at its recommendation. In this paper we introduce PeerChooser, a collaborative recommender system with an interactive interface which provides the user not only an explanation of the recommendation process, but the opportunity to manipulate a graph of their peers at varying levels of granularity, to reflect aspects of their current requirements. PeerChooser's prediction component reads directly from the graph to yield the same results as a benchmark recommendation algorithm. Users then improve on these predictions by tweaking the graph in various ways. PeerChooser compares favorably against the benchmark in live evaluations and equally well in automated accuracy tests. |
| Starting Page | 74 |
| Ending Page | 81 |
| File Size | 888891 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424453344 |
| DOI | 10.1109/CSE.2009.26 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-08-29 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Recommender Systems Visualization Collaborative Filtering Information filtering Clustering Computer science Mood Feedback Collaboration Benchmark testing Motion pictures Information filters Books Recommender systems |
| Content Type | Text |
| Resource Type | Article |
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