1Dell1 Amico M, Capra L. Dependable filtering philoso-phy and realizations [J]. ACM Transactions on Informa-tion Systems(TOIS), 2010,29( 1) : 364-371.
2Vallet D, Hopfgartner F, Jose J M, et al. Effects ofusage-based feedback on video retrieval: a simulation-based study [J]. ACM Transactions on Information Sys-tems (TOIS),2011,29(2):219-230.
5AGRAWAL R, SRIKANT R. Mining Sequential Patterns[A]. Proceedings International Conference on Data Engineering( ICDE 95)[C].1995.3 -14.
6CHEN MS, PARK JS, YU PS. Efficient Data Mining for Path Traversal Patterns[A]. IEEE Transactions on Knowledge and Data Engineering[C]. 1998,10(2): 209 -221.
7PEI J. HAN J, MORTAZAVI-ASL B, et al. Mining Acccess Patterns Efficiently from Web Logs[A]. Proceedings Pacific - Asia Conference on Know ledge Discovery and Data Mining(PaKDD)[C]. Kyoto, Japan, 2000. 396 -407.
8Agrawal R, Srikant R. Mining sequential patterns [C]//Procee: dings of the Eleventh International Conference on Data Engi- neering( ICDE ' 95 ). Washington, DC: IEEE Computer Society, 1995:3-14.
9Srikant R, Agrawal R. Mining sequential patterns: generaliza- tions and performance improvements[C]//Proceedings of the 5th International Conference on Extending Database Technolo- gy Advances in Database Technology (EDBT' 96 ). Berlin: Springer-Verlag, 1996 : 3-17.
10Han J, Pei J, Mortazviasl B, et al. FreeSpan: Frequent pattern projected sequential pattern mining[C]//Proceedings of the 6th ACM-SIGKDD International Conference on Knowledge Disco very and Data Mining. New York: ACM Press, 2000:355-359.
