Data Mining: The Textbook

Cambridge University Press, Cambridge, 2008.

375. 
     M. Markou, and S. Singh. Novelty detection: a review, part 1: statistical approaches. Signal Processing, 83(12), pp. 2481–2497, 2003.
     

375. 
     G. J. McLachian. Discriminant analysis and statistical pattern recognition. Wiler Interscience, 2004.
     

375. 
     M. Markou, and S. Singh. Novelty detection: A review, part 2: neural network-based approaches. Signal Processing, 83(12), pp. 2481–2497, 2003.
     

375. 
     M. Mehta, R. Agrawal, and J. Rissanen. SLIQ: A fast scalable classifier for data mining, EDBT Conference, pp. 18–32, 1996.
     

375. 
     P. Melville, M. Saar-Tsechansky, F. Provost, and R. Mooney. An expected utility approach to active feature-value acquisition. IEEE ICDM Conference, 2005.
     

375. 
     A. K. Menon, and C. Elkan. Link prediction via matrix factorization. Machine Learn-ing and Knowledge Discovery in Databases, pp. 437–452, 2011.
     

375. 
     B. Messmer, and H. Bunke. A new algorithm for error-tolerant subgraph isomprohism detection. IEEE Transactions on Pattern Mining and Machine Intelligence, 20(5),
     
     42. 
         493–504, 1998.
         

375. 
     A. Meyerson, and R. Williams. On the complexity of optimal k-anonymization. ACM PODS Conference, pp. 223–228, 2004.
     

375. 
     R. Michalski, I. Mozetic, J. Hong, and N. Lavrac. The multi-purpose incremental learning system AQ15 and its testing application to three medical domains. Proceed-ings of the AAAI, pp. 1–41, 1986.
     

375. 
     C. Michael, and A. Ghosh. Two state-based approaches to program-based anomaly detection. Computer Security Applications Conference, pp. 21, 2000.
     

375. 
     H. Miller, and J. Han. Geographic data mining and knowledge discovery. CRC Press, 2009.
     

375. 
     T. M. Mitchell. Machine learning. McGraw Hill International Edition, 1997.
     

375. 
     B. Mobasher. Web usage mining and personalization. Practical Handbook of Internet Computing, ed. Munindar Singh, pp, 264–265, CRC Press, 2005.
     

375. 
     D. Montgomery, E. Peck, and G. Vining. Introduction to linear regression analysis.
     

John Wiley and Sons, 2012.

375. 
     C. H. Mooney, and J. F. Roddick. Sequential pattern mining: approaches and algo-rithms. ACM Computing Surveys (CSUR), 45(2), 2013.
     

BIBLIOGRAPHY

717

393. 
     B. Moret. Decision trees and diagrams. ACM Computing Surveys (CSUR), 14(4),
     

42. 
    593–623, 1982.
    

393. 
     A. Mueen, E. Keogh, Q. Zhu, S. Cash, and M. Westover. Exact discovery of time series motifs. SDM Conference, pp. 473–484, 2009.
     

393. 
     A. Mueen, and E. Keogh. Online discovery and maintenance of time series motifs. ACM KDD Conference, pp. 1089–1098, 2010.
     

393. 
     E. Muller, M. Schiffer, and T. Seidl. Statistical selection of relevant subspace projec-tions for outlier ranking. ICDE Conference, pp, 434–445, 2011.
     

393. 
     E. Muller, I. Assent, P. Iglesias, Y. Mulle, and K. Bohm. Outlier analysis via subspace analysis in multiple views of the data. IEEE ICDM Conference, pp. 529–538, 2012.
     

393. 
     S. K. Murthy. Automatic construction of decision trees from data: A multi-disciplinary survey. Data Mining and Knowledge Discovery, 2(4), pp. 345–389, 1998.
     

393. 
     S. Nabar, K. Kenthapadi, N. Mishra, and R. Motwani. A survey of query auditing techniques for data privacy. Privacy-Preserving Data Mining: Models and Algorithms, Springer, pp. 415–431, 2008.
     

393. 
     D. Nadeau, and S. Sekine. A survey of named entity recognition and classification.