Open Access
Issue
MATEC Web of Conferences
Volume 22, 2015
International Conference on Engineering Technology and Application (ICETA 2015)
Article Number 01034
Number of page(s) 6
Section Information and Communication Technology
DOI https://doi.org/10.1051/matecconf/20152201034
Published online 09 July 2015
  1. X. Amatriain. 2013. Mining large streams of user data for personalized recommendations. ACM SIGKDD Explorations Newsletter, 14(2): 37–48. [CrossRef] [Google Scholar]
  2. K. Chen, T. Chen, G. Zheng, O. Jin, E. Yao. & Y. Yu. 2012. Collaborative personalized tweet recommendation. In Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM. pp: 661–670. [Google Scholar]
  3. P. Cremonesi, Y. Koren. & R. Turrin. 2010. Performance of recommender algorithms on top-n recommendation tasks. In Proceedings of the Fourth ACM Conference on Recommender Systems, ACM. pp: 39–46. [Google Scholar]
  4. M. Kurucz, A. A. Benczur, T. Kiss, I. Nagy, A. Szabó, & B.Torma. 2007. Who rated what: A combination of SVD, correlation and frequent sequence mining. In Proc. KDD Cup and Workshop, Citeseer. 23: 720–727. [Google Scholar]
  5. X. Liu. & K. Aberer. 2013. Soco: a social network aided context-aware recommender system. In Proceedings of the 22nd International Conference on World Wide Web, International World Wide Web Conferences Steering Committee. pp: 781–802. [Google Scholar]
  6. H. Ma, D. Zhou, C. Liu, M. R. Lyu. & I. King. 2011. Recommender systems with social regularization. In Proceedings of the Fourth ACM International Conference on Web Search and Data Mining, ACM. pp: 287–296. [Google Scholar]
  7. A. Mnih & R. Salakhutdinov. 2007. Probabilistic matrix factorization. In Advances in Neural Information Processing Systems, pp: 1257–1264. [Google Scholar]
  8. R. Pan, Y. Zhou, B. Cao, N. N. Liu, R. Lukose, M. Scholz. & Q. Yang. 2008. One-class collaborative filtering. In Data Mining, 2008. ICDM’08. Eighth IEEE International Conference on, IEEE. pp: 502–511. [Google Scholar]
  9. S. Rendle, C. Freudenthaler, Z. Gantner, & L. Schmidt-Thieme. 2009. BPR: Bayesian personalized ranking from implicit feedback. In Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, AUAI Press. pp: 452–461. [Google Scholar]
  10. B. Sarwar, G. Karypis, J. Konstan, & J. Riedl. 2001. Item-based collaborative filtering recommendation algorithms. In Proceedings of the 10th International Conference on World Wide Web, ACM. pp: 285–295. [Google Scholar]
  11. Y. Shi, A. Karatzoglou, L. Baltrunas, M. Larson, A. Hanjalic. & N. Oliver. 2012. TFMAP: Optimizing map for top-n context-aware recommendation. In Proceedings of the 35th international ACM SIGIR Conference on Research and Development in Information Retrieval, ACM. pp: 155–164. [Google Scholar]
  12. X. Yang, H. Steck. & Y. Liu. 2012. Circle-based recommendation in online social networks. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM. pp: 1267–1275. [Google Scholar]
  13. E. Zhong, W. Fan, J. Wang, L. Xiao. & Y. Li. 2012. Comsoc: adaptive transfer of user behaviors over composite social network. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM. pp: 696–704. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.