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Gabor Melli has done an interesting analysis of papers from the past
KDD conferences and what were the most common citations/
Here are the top references with at least 20 citations (combined) from KDD-2008, KDD-2009, KDD-2010, KDD-2011
| Total Citations | Reference |
| 51 | David M. Blei, Andrew Y. Ng, and Michael I. Jordan. (2003). "Latent Dirichlet Allocation." In: The Journal of Machine Learning Research, 3. doi:10.1162/jmlr.2003.3.4-5.993 |
| 33 | Chih-Chung Chang, and Chih-Jen Lin. (2001). LIBSVM: a library for support vector machines. Technical Report. |
| 26 | Arthur Asuncion and David J. Newman 2007 UCI Machine Learning Repository . Irvine, CA: University of California, School of Information and Computer Science. |
| 23 | Trevor Hastie, Robert Tibshirani, and Jerome H. Friedman. (2001). The Elements of Statistical Learning: Data Mining, Inference, and Prediction; 1st edition. Springer-Verlag. ISBN 0387952845 |
| 22 | Jon Kleinberg. (1999). Authoritative Sources in a Hyperlinked Environment. In: Journal of the ACM (JACM), 46(5) doi:10.1145/324133.324140 |
| 21 | Thomas L. Griffiths, and Mark Steyvers. (2004). Finding Scientific Topics. In: Proceedings of the National Academy of Sciences (PNAS), 101(Suppl. 1). doi:10.1073/pnas.0307752101 |
| 20 | 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 |
| 20 | Ian H. Witten and Eibe Frank. Data Mining: Practical Machine Learning Tools and Techniques, Second Edition. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 2005. |
The full results are at