References

Ayres, J., J. Flannick, J. Gehrke and T. Yiu, 2002. Sequential pattern mining using a bitmap representation. Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, July 23-25, 2002, New York, USA., pp: 429-435.

Eduardo, M. and A. Brea, 2013. Constrained clustering algorithms: Practical issues and applications. Ph.D Thesis, University of Coruna, Coruna, Spain.

Feno, D.R., 2007. Quality measures of the association rules: Standardization and characterization of the bases. Ph.D Thesis, University of La Réunion, Saint-Denis, France.

Fontaine, M.D., 2008. From artificial learning to human learning: From trace harvesting to user modeling. Ph.D Thesis, Universite Pierre et Marie Curie-Paris, Paris, France.

Fournier, V.P., 2010. A hybrid model for learning support in procedural and ill-defined domains. Ph.D Thesis, Universite du Quebec a Montreal, Montreal, Quebec.

Guha, S., R. Rastogi and K. Shim, 1999. ROCK: A robust clustering algorithm for categorical attributes. Proceedings of the 15th International Conference on Data Engineering, March 23-26, 1999, Sydney, Australia, pp: 512-521.

Hay, B., G. Wets and K. Vanhoof, 2004. Mining navigation patterns using a sequence alignment method. Knowl. Inf. Syst., 6: 150-163.
CrossRef  |  Direct Link  |  

Kam, P.S. and A.W.C. Fu, 2000. Discovering Temporal Patterns for Interval-Based Events. In: Data Warehousing and Knowledge Discovery, Kambayashi, Y., M. Mohania and A.M. Tjoa (Eds.). Springer, Berlin, Germany, pp: 317-326.

Karkkainen, T. and S. Ayramo, 2006. Introduction to partitioning-based clustering methods with a robust example. Master Thesis, University of Jyvaskyla, Jyvaskyla, Finland.

Kashef, R., 2008. Cooperative clustering model and its applications. Ph.D Thesis, University of Waterloo, Waterloo, Ontario.

Koskela, M., J. Laaksonen and E. Oja, 2004. Entropy-based measures for clustering and SOM topology preservation applied to content-based image indexing and retrieval. Proceedings of the 17th International Conference on Pattern Recognition, Vol. 2, August 26, 2004, IEEE, New York, USA., ISBN: 0-7695-2128-2, pp: 1005-1008.

Liu, B., 2007. Web Data Mining: Exploring Hyperlinks, Contents and Usage Data. Springer, Berlin, Germany, ISBN:13-978-3-540-37881-5, Pages: 531.

Marascu, A., 2009. Extracting sequential patterns in data streams. Ph.D Thesis, Universite Nice Sophia Antipolis, Nice, France.

Masseglia, F., P. Poncelet and R. Cicchetti, 2000. An efficient algorithm for web usage mining. Networking Inf. Syst. J., 2: 571-604.
Direct Link  |  

Meger, N., 2004. Automatic search for optimal time windows in sequential patterns. Ph.D Thesis, University of Louisville, Louisville, Kentucky.

Pei, J., J. Han, M.A. Behzad, P. Helen, Q. Chen and M.C. Hsu, 2001. PrefixSpan,: Mining sequential patterns efficiently by prefix-projected pattern growth. Proceedings of the 17th International Conference on Data Engineering, April 2-6, 2001, Heidelberg, Germany, pp: 215-224.

Pham, T.T., J.W. Luo, T.P. Hong and B. Vo, 2013. An efficient algorithm for mining sequential rules with interestingness measures. Intl. J. Innov. Comput. Inf. Control., 9: 4811-4824.
Direct Link  |  

Poornalatha, G. and S.R. Prakash, 2013. Web sessions clustering using hybrid sequence alignment measure (HSAM). Soc. Network Anal. Min., 3: 257-268.
CrossRef  |  Direct Link  |  

Poulose, J., 2013. Development of hierarchical clustering techniques for gridded. Master Thesis, University of CUSAT, South Kalamassery, India.

Rosenberg, A. and J. Hirschberg, 2007. V-Measure: A conditional entropy-based external cluster evaluation measure. Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, June 28-30, 2007, Association for Computational Linguistics, Prague, Czech Republic, pp: 410-420.

Saneifar, H., S. Bringay and T.M. Maguelonne, 2009. S2MP: A similarity measure for sequential patterns. Proceedings of the International Conference on Evaluation Methods of Knowledge Extraction in Data, February 27, 2009, Montpellier 2 University, Montpellier, France, pp: 5-46.

Silva, D.A.G., 2009. Scalable data analysis: Application to web usage data. Ph.D Thesis, Paris Dauphine University, Paris, France.

Zaki, M.J., 2001. SPADE: An efficient algorithm for mining frequent sequences. Mach. Learn. J., 42: 31-60.
CrossRef  |  Direct Link  |  

Zhao, Q., 2012. Cluster validity in clustering methods. Ph.D. Thesis, University of Eastern Finland, Finland.