Semi-supervised correction of biased comment ratings

WWW'12 - Proceedings of the 21st Annual Conference on World Wide Web

Volumn , Issue , 2012, Pages 181-190

  Mishra, Abhinav ^a   Rastogi, Rajeev ^a  

^a YAHOO RESEARCH   (United States)

Author keywords

Active learning; Bias; Iterative technique; Semi supervised learning

Indexed keywords

ACTIVE LEARNING; ACTIVE LEARNING METHODS; ACTIVE-LEARNING ALGORITHM; BIAS; DATA SETS; EMPIRICAL RISK MINIMIZATION; FIXED POINTS; ITERATIVE TECHNIQUE; RUNNING TIME; SEMI-SUPERVISED; SEMI-SUPERVISED LEARNING; SEMI-SUPERVISED LEARNING TECHNIQUES; USER RATING;

ITERATIVE METHODS; LEARNING ALGORITHMS; WORLD WIDE WEB;

SUPERVISED LEARNING;

EID: 84860859180     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2187836.2187862     Document Type: Conference Paper

References (29)

1. D. Agarwal, B.-C. Chen, and B. Pang. Personalized recommendation of user comments via factor models. In EMNLP, 2011.
2. M. Bilgic, L. Mihalkova, and L. Getoor. Active learning for networked data. In ICML, 2010.
3. A. Blum and S. Chawla. Learning from labeled and unlabeled data using graph mincuts. In ICML, 2001.
4. S. Brin and L. Page. The anatomy of a large-scale hypertextual web search engine. Computer Networks, 30(1-7):107-117, 1998.
5. N. Cesa-Bianchi, C. Gentile, F. Vitale, and G. Zappella. Active learning on trees and graphs. In COLT, 2010.
6. B.-C. Chen, J. Guo, B. Tseng, and J. Yang. User reputation in a comment rating environment. In KDD, 2011.
7. N. Diakopoulos and M. Naaman. Topicality, time and sentiment in online news comments. In CHI EA'11, 2011.
8. N. Diakopoulos and M. Naaman. Towards quality discourse in online news comments. In CSCW, 2011.
9. A. Guillory and J. Bilmes. Label Selection on Graphs. In NIPS. 2009.
10. C.-F. Hsu, E. Khabiri, and J. Caverlee. Ranking comments on the social web. In ICCSE, 2009.
11. S. Kiesler, J. Siegel, and W. McGuire, Timothy.Computer-supported cooperative work: a book of readings.chapter Social psychological aspects of computer-mediatedcommunication (Reprint), pages 657-682. Morgan Kaufmann Publishers Inc., 1988.
12. J. M. Kleinberg. Authoritative sources in a hyperlinked environment. J. ACM, 46(5):604-632, 1999.
13. Y. Koren. Factorization meets the neighborhood: a multifaceted collaborative filtering model. In KDD, 2008.
14. C. Lampe and P. Resnick. Slash(dot) and burn: distributed moderation in a large online conversation space. In CHI, 2004.
15. C. A. Lampe, E. Johnston, and P. Resnick. Follow the reader: filtering comments on slashdot. In CHI, 2007.
16. H. W. Lauw, E.-P. Lim, and K. Wang. Bias and controversy: beyond the statistical deviation. In KDD, 2006.
17. H. W. Lauw, E.-P. Lim, and K. Wang. Summarizing review scores of "unequal" reviewers. In SDM, 2007.
18. S. A. Macskassy. Using graph-based metrics with empirical risk minimization to speed up active learning on networked data. In KDD, 2009.
19. K. Purcell, L. Purcell, A. Mitchell, T. Rosenstiel, and K. Olmstead. Understanding the participatory news consumer. Pew Internet and American Life Project, 2010.
20. N. Roy and A. McCallum. Toward optimal active learning through sampling estimation of error reduction. In ICML, 2001.
21. B. Settles. Active learning literature survey. Computer Sciences Technical Report 1648, University of Wisconsin-Madison, 2009.
22. S. Siersdorfer, S. Chelaru, W. Nejdl, and J. S. Pedro. How useful are your comments?: analyzing and predicting youtube comments and comment ratings. In WWW, 2010.
23. G. W. Stewart. Matrix Algorithms: Volume 1, Basic Decompositions. Society for Industrial Mathematics, 1998.
24. D. M. Strong, Y. W. Lee, and R. Y. Wang. Data quality in context. Commun. ACM, 40:103-110, May 1997.
25. V. G. V. Vydiswaran, C. Zhai, and D. Roth. Content-driven trust propagation framework. In KDD, 2011.
26. X. Yin, J. Han, and P. S. Yu. Truth discovery with multiple conflicting information providers on the web. IEEE Trans. Knowl. Data Eng., 20(6):796-808, 2008.
27. A. X. Zheng, A. Y. Ng, and M. I. Jordan. Stable algorithms for link analysis. In SIGIR, 2001.
28. X. Zhu, Z. Ghahramani, and J. D. Lafferty. Semi-supervised learning using gaussian fields and harmonic functions. In ICML, 2003.
29. X. Zhu, J. Lafferty, and Z. Ghahramani. Combining active learning and semi-supervised learning using gaussian fields and harmonic functions. In ICML 2003 workshop on The Continuum from Labeled to Unlabeled Data in Machine Learning and Data Mining, pages 58-65, 2003.