Finding sequential patterns with TF-IDF metrics in health-care databases

[1] R. Agrawal, R. Srikant, Mining sequential patterns, Proc. Eleventh International Conference on Data Engineering, Taipei, Taiwan, 1995, pp. 3-14. ⇒300Search in Google Scholar

[2] L. M. Aouad, Nhien-An Le-Khac, T. M. Kechadi, Performance study of distributed apriori-like frequent itemsets mining, Knowledge and Information Systems, 23, 1 (2009) 55-72. ⇒30010.1007/s10115-009-0205-3Search in Google Scholar

[3] J. Ayres, J. Gehrke, T. Yiu, J. Flannick, Sequential pattern mining using bitmaps, Proc. Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Edmonton, Canada, July 2002, pp. 429-435. ⇒29110.1145/775047.775109Search in Google Scholar

[4] P. Fournier-Viger, SPMF - an open-source data mining library, 2014. ⇒ 291, 306Search in Google Scholar

[5] T. Z. Gál, G. Kovács, Z. T. Kardkovács, Survey on privacy preserving data mining techniques in health care databases, Acta Univ. Sapientiae, Informatica, 6, 1 (2014) 33-55. ⇒30510.2478/ausi-2014-0017Search in Google Scholar

[6] L. Geng, H. J. Hamilton, Interestingness measures for data mining: A survey, ACM Computing Surveys (CSUR), 38, 3 (2006) ⇒292, 293, 29410.1145/1132960.1132963Search in Google Scholar

[7] K. Gouda, M. Hassaan, Mining sequential patterns in dense databases, International Journal of Database Management Systems (IJDMS), 3, 1 (2011) 179-194. ⇒29110.5121/ijdms.2011.3112Search in Google Scholar

[8] J. Han, J. Pei, Y. Yin, Mining frequent patterns without candidate generation, Proc. International Conference Management of Data (ACM-SIGMOD ’00), Dallas, USA, May 2000, pp. 1-12. ⇒29010.1145/335191.335372Search in Google Scholar

[9] T. P. Hong, C. W. Lin, K. T. Yang, S. L. Wang, A heuristic data-sanitization approach based on TF-IDF, Proc. 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, Lecture Notes in Artificial Intelligence 6703 (2011) 156-164. ⇒30110.1007/978-3-642-21822-4_17Search in Google Scholar

[10] K. McGarry, A survey of interestingness measures for knowledge discovery, The Knowledge Engineering Review, 20, 1 (2005) 39-61. ⇒29210.1017/S0269888905000408Search in Google Scholar

[11] P. W. Purdom, D. Van Gucht , D. P. Groth, Average-case performance of the apriori algorithm, SIAM Journal on Computing, 33, 5 (2004) 1223-1260. ⇒30010.1137/S0097539703422881Search in Google Scholar

[12] G. Salton, E. A. Fox, H. Wu, Extended boolean information retrieval, Communications of ACM, 26, 12 (1983) 1022-1036. ⇒288, 30110.1145/182.358466Search in Google Scholar

[13] R. Srikant, R. Agrawal, Mining sequential patterns: Generalizations and performance improvements, Proc. 5th International Conference on Extending Database Technology: Advances in Database Technology (EDBT ’96), Lecture Notes in Security and Cryptology 1057, (1996) 3-17. ⇒29010.1007/BFb0014140Search in Google Scholar

[14] Y. Tabei, An imprementation of PrefixSpan (prefix-projected sequential pattern mining), 2008. ⇒306Search in Google Scholar

[15] M. J. Zaki, SPADE: An efficient algorithm for mining frequent sequences, Machine Learning, 42, 1-2 (2001) 31-60. ⇒290, 295 10.1023/A:1007652502315Search in Google Scholar