KDD 2010 References Analysis Report
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A KDD-2010 References Analysis Report is a KDD references analysis report for the KDD 2010 Proceedings.
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- See: ACM Digital Library, Bibliometric Analysis.
References
2011-08-13 KDD 2010 References Analysis Report
(note: this data was extracted semi-automatically so there are likely some inaccuracies).
| Row Identifier | References Count Rank | References Count | Referenced Publication (short + hyperlink) | Referenced Publication (full citation string) |
|---|---|---|---|---|
| 1 | 1 | 13 | (Asuncion & Newman, 2007) | Arthur Asuncion and David J. Newman 2007 UCI Machine Learning Repository {http://www.ics.uci.edu/~mlearn/MLRepository.html}. Irvine, CA: University of California, School of Information and Computer Science. |
| 2 | 2 | 12 | (Blei, Ng & Jordan, 2003)[1] | David M. Blei, Andrew Y. Ng, Michael I. Jordan, Latent dirichlet allocation. In: The Journal of Machine Learning Research, 3, p.993-1022, 3/1/2003 doi:10.1162/jmlr.2003.3.4-5.993 |
| 3 | 3 | 9 | (Chang & Lin, 2001) | Chih-Chung Chang and C.-J. Lin. LIBSVM: A library for support vector machines, 2001. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm. |
| 4 | 4 | 7 | (Kempe et al., 2003) | David Kempe, Jon M. Kleinberg, Éva Tardos, Maximizing the spread of influence through a social network. In: Proceedings of the ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 24-27, 2003, Washington, D.C. doi:10.1145/956750.956769 |
| 5 | 5 | 6 | (Griffiths & Steyvers, 2004) | Thomas L. Griffiths and Mark Steyvers. Finding scientific topics. In: Proceedings of the National Academy of Sciences of the United States of America, 101 Suppl:5228--35, April 2004. |
| 6 | 5 | 6 | (Leskovec et al., 2009) | Jure Leskovec, Lars Backstrom, Jon M. Kleinberg, Meme-tracking and the dynamics of the news cycle. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, June 28-July 01, 2009, Paris, France doi:10.1145/1557019.1557077 |
| 7 | 5 | 6 | (Liben-Nowell & Kleinberg, 2003) | David Liben-Nowell, Jon M. Kleinberg, The link prediction problem for social networks. In: Proceedings of the twelfth International Conference on Information and knowledge management, November 03-08, 2003, New Orleans, LA, USA doi:10.1145/956863.956972 |
| 8 | 6 | 5 | (Domingos & Richardson, 2001) | Pedro Domingos, Matt Richardson, Mining the network value of customers. In: Proceedings of the seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, p.57-66, August 26-29, 2001, San Francisco, California doi:10.1145/502512.502525 |
| 9 | 6 | 5 | (Gruhl et al., 2004) | Daniel Gruhl, R. Guha, David Liben-Nowell, Andrew Tomkins, Information diffusion through blogspace. In: Proceedings of the 13th International Conference on World Wide Web, May 17-20, 2004, New York, NY, USA doi:10.1145/988672.988739 |
| 10 | 7 | 4 | (Bishop, 2006) | Christopher M. Bishop, Pattern Recognition and Machine Learning (Information Science and Statistics). Springer-Verlag New York, Inc., Secaucus, NJ, 2006 |
| 11 | 7 | 4 | (Blei & Lafferty, 2006) | David M. Blei, John D. Lafferty, Dynamic topic models. In: Proceedings of the 23rd International Conference on Machine learning, p.113-120, June 25-29, 2006, Pittsburgh, Pennsylvania doi:10.1145/1143844.1143859 |
| 12 | 7 | 4 | (Boyd & Vandenberghe, 2004) | Stephen Boyd, Lieven Vandenberghe, Convex Optimization, Cambridge University Press, New York, NY, 2004 |
| 13 | 7 | 4 | (Breiman, 1996) | Leo Breiman, Bagging predictors, Machine Learning, v.24 n.2, p.123-140, Aug. 1996 doi:10.1023/A:1018054314350 |
| 14 | 7 | 4 | (Breiman, 2001) | Leo Breiman, Random Forests, Machine Learning, v.45 n.1, p.5-32, October 1 2001 doi:10.1023/A:1010933404324 |
| 15 | 7 | 4 | (Caruana, 1997) | Rich Caruana, Multitask Learning, Machine Learning, v.28 n.1, p.41-75, July 1997 doi:10.1023/A:1007379606734 |
| 16 | 7 | 4 | (Chandola et al., 2007) | Varun Chandola, Arindam Banerjee, Vipin Kumar, Anomaly detection: A survey. In: ACM Computing Surveyss (CSUR), v.41 n.3, p.1-58, July 2009 doi:10.1145/1541880.1541882 |
| 17 | 7 | 4 | (Dempster et al., 1977) | Arthur P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelihood from incomplete data via the em algorithm. In: Journal of Royal Statistical Society. Series B (Methodological), 39:1--38, 1977. |
| 18 | 7 | 4 | (Girvan & Newman, 2002) | Michelle Girvan and M. E. J. Newman. Community structure in social and biological networks. In: Proceedings of the National Academy of Sciences of the USA, 99(12):7821--7826, 2002. |
| 19 | 7 | 4 | (Guyon & Elisseeff, 2003) | Isabelle Guyon, André Elisseeff, An introduction to variable and feature selection. In: The Journal of Machine Learning Research, 3, 3/1/2003 |
| 20 | 7 | 4 | (Hastie et al., 2001)[2] | Trevor Hastie, Robert Tibshirani, and J. Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer, New York, NY, 2nd edition, 2009. |
| 21 | 7 | 4 | (Kleinberg, 1999) | Jon M. Kleinberg, Authoritative sources in a hyperlinked environment. In: Journal of the ACM (JACM), v.46 n.5, p.604-632, Sept. 1999 doi:10.1145/324133.324140 |
| 22 | 7 | 4 | (Kleinberg, 2002) | Jon M. Kleinberg, Bursty and hierarchical structure in streams. In: Proceedings of the eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, July 23-26, 2002, Edmonton, Alberta, Canada doi:10.1145/775047.775061 |
| 23 | 7 | 4 | (Koren, 2009) | Yehuda Koren, Collaborative filtering with temporal dynamics. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, June 28-July 01, 2009, Paris, France doi:10.1145/1557019.1557072 |
| 24 | 7 | 4 | (Lafferty et al., 2001) | John D. Lafferty, Andrew McCallum, Fernando C. N. Pereira, Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. In: Proceedings of the Eighteenth International Conference on Machine Learning, p.282-289, June 28-July 01, 2001 |
| 25 | 7 | 4 | (Leskovec, Krause et al., 2007) | Jure Leskovec, Andreas Krause, Carlos Guestrin, Christos Faloutsos, Jeanne VanBriesen, Natalie Glance, Cost-effective outbreak detection in networks. In: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 12-15, 2007, San Jose, California, USA doi:10.1145/1281192.1281239 |
| 26 | 7 | 4 | (Ng, Jordan & Weiss, 2001) | Andrew Y. Ng, Michael I. Jordan, and Yair Weiss. On spectral clustering: Analysis and an algorithm. In: Advances in Neural Information Processing Systems 14, pages 849--856. MIT Press, Cambridge, MA, 2001. |
| 27 | 7 | 4 | (Page et al., 1998) | Lawrence Page, Sergey Brin, Rajeev Motwani, and T. Winograd. The pagerank citation ranking: Bringing order to the web. Technical report, Stanford University Database Group, http://citeseer.nj.nec.com/368196.html, 1998. |
| 28 | 7 | 4 | (Quinlan, 1993a) | J. Ross Quinlan, C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers Inc., San Francisco, CA, 1993 |
| 29 | 7 | 4 | (Richardson et al., 2007) | Matthew Richardson, Ewa Dominowska, Robert Ragno, Predicting clicks: estimating the click-through rate for new ads. In: Proceedings of the 16th International Conference on World Wide Web, May 08-12, 2007, Banff, Alberta, Canada doi:10.1145/1242572.1242643 |
| 30 | 7 | 4 | (Shi & Malik, 2000) | Jianbo Shi, Jitendra Malik, Normalized Cuts and Image Segmentation. In: IEEE Transactions on Pattern Analysis and Machine Intelligence, v.22 n.8, p.888-905, August 2000 doi:10.1109/34.868688 |
| 31 | 7 | 4 | (Tibshirani, 1996) | Robert Tibshirani. Regression shrinkage and selection via the lasso. In: Journal of the Royal Statistical Society. Series B, 58(1):267--288, 1996. |
| 32 | 7 | 4 | (Vapnik, 1995) | Vladimir N. Vapnik, The nature of statistical learning theory. Springer-Verlag New York, Inc., New York, NY, 1995 |
| 33 | 7 | 4 | (Wagstaff et al., 2001) | Kiri Wagstaff, Claire Cardie, Seth Rogers, Stefan Schrödl, Constrained K-means Clustering with Background Knowledge. In: Proceedings of the Eighteenth International Conference on Machine Learning, p.577-584, June 28-July 01, 2001 |
| 34 | 7 | 4 | (Wang & McCallum, 2006) | Xuerui Wang, Andrew McCallum, Topics over time: a non-Markov continuous-time model of topical trends. In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 20-23, 2006, Philadelphia, PA, USA doi:10.1145/1150402.1150450 |
| 35 | 7 | 4 | (Yang & Pedersen, 1997) | Yiming Yang, Jan O. Pedersen, A Comparative Study on Feature Selection in Text Categorization. In: Proceedings of the Fourteenth International Conference on Machine Learning, p.412-420, July 08-12, 1997 |
| 3,010 | Total Reference Items (entire proceedings) |