@INPROCEEDINGS{guo2013novel, author = {Guo, G. and Zhang, J. and Yorke-Smith, N.}, title = {A Novel Bayesian Similarity Measure for Recommender Systems}, booktitle = {Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI)}, year = {2013}, pages = {2619-2625} }
@INPROCEEDINGS{guo2014etaf, author = {Guo, G. and Zhang, J. and Thalmann, D. and Yorke-Smith, N.}, title = {ETAF: An Extended Trust Antecedents Framework for Trust Prediction}, booktitle = {Proceedings of the 2014 International Conference on Advances in Social Networks Analysis and Mining (ASONAM)}, pages = {540-547}, year = {2014} }
Data Set | Basic Meta | User Context | Other Contexts | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Users | Items | Ratings (Scale) | Density | Users | Links (Type) | Items | Labels | |||
Ciao | 7,375 | 99,746 | 278,483 | [1, 5] | 0.0379% | 7,375 | 111,781 | Trust | General | |
Douban | 129,490 | 58,541 | 16,830,839 | [1, 5] | 0.222% | 129,490 | 1,692,952 | Friendship | Movie | |
Epinions (665K) | 40,163 | 139,738 | 664,824 | [1, 5] | 0.0118% | 49,289 | 487,183 | Trust | General | |
Epinions (510K) | 71,002 | 104,356 | 508,960 | [1, 5] | 0.00687% | Trust | General | |||
Epinions (Extended) | 120,492 | 755,760 | 13,668,320 | [1, 5] | 0.015% | Trust Distrust |
General | |||
Flixster | 147,612 | 48,794 | 8,196,077 | [0.5, 5.0] | 0.1138% | 787,213 | 11,794,648 | Friendship | Movie | |
FilmTrust | 1,508 | 2,071 | 35,497 | [0.5, 4.0] | 1.14% | 1,642 | 1,853 | Trust | Movie | |
Jester | 59,132 | 140 | 1,761,439 | Explicit | 21.28% | Joke | ||||
MovieLens 100K | 943 | 1,682 | 100,000 | [1, 5] | 6.30% | Movie | Tag | |||
MovieLens 1M | 6,040 | 3,706 | 1,000,209 | [1, 5] | 4.47% | Movie | Tag | |||
MovieLens 10M | 71,567 | 10,681 | 10,000,054 | [1, 5] | 1.308% | Movie | Tag |