Detecting anomalies in dynamic rating data: A robust probabilistic model for rating evolution

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2014, Pages 841-850

  Günnemann, Stephan ^a   Günnemann, Nikou ^a   Faloutsos, Christos ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

anomaly detection; categorical mixtures; robust mining

Indexed keywords

EID: 84907029495     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2623330.2623721     Document Type: Conference Paper

References (18)

1. C. C. Aggarwal. Outlier Analysis. Springer, 2013.
2. A. Ahmed and E. P. Xing. Timeline: A dynamic hierarchical dirichlet process model for recovering birth/death and evolution of topics in text stream. In UAI, pages 20-29, 2010.
3. F. Bengtsson et al. Computing maximum-scoring segments in almost linear time. In Computing and Combinatorics, pages 255-264. Springer, 2006.
4. J. Bentley. Programming pearls: algorithm design techniques. Communications of the ACM, 27(9):865-873, 1984.
5. C. M. Bishop. Pattern recognition and machine learning. Springer, 2007.
6. D. M. Blei and J. D. Lafferty. Dynamic topic models. In ICML, pages 113-120, 2006.
7. N. Günnemann, S. Günnemann, and C. Faloutsos.Robust multivariate autoregression for anomaly detection in dynamic product ratings. In WWW, pages 361-372, 2014.
8. N. Jindal and B. Liu. Opinion spam and analysis. In WSDM, pages 219-230, 2008.
9. N. Koenigstein, G. Dror, and Y. Koren. Yahoo! music recommendations: modeling music ratings with temporal dynamics and item taxonomy. In RecSys, pages 165-172, 2011.
10. Y. Koren. Collaborative filtering with temporal dynamics. In KDD, pages 447-456, 2009.
11. G. F. Lawler. Introduction to stochastic processes. CRC Press, 2006.
12. K. Lerman. Dynamics of a collaborative rating system. In WebKDD/SNA-KDD, pages 77-96, 2007.
13. R. B. Litterman. Forecasting with bayesian vector autoregressions. Journal of Business & Economic Statistics, 4(1):25-38, 1986.
14. H. Lütkepohl. New introduction to multiple time series analysis. Cambridge University Press, 2005.
15. X. Song, M. Wu, C. M. Jermaine, and S. Ranka. Statistical change detection for multi-dimensional data. In KDD, pages 667-676, 2007.
16. J.-A. Ting, E. Theodorou, and S. Schaal. Learning an outlier-robust kalman filter. In ECML, pages 748-756, 2007.
17. C. Wang, D. M. Blei, and D. Heckerman. Continuous time dynamic topic models. In UAI, pages 579-586, 2008.
18. H. Wang, Y. Lu, and C. Zhai. Latent aspect rating analysis on review text data: a rating regression approach. In KDD, pages 783-792, 2010.