Citation: | You Yuyang, Zhang Jianpei, Yang Zhihong, et al. Construction of fault-tolerant synopsis over data stream based on prefix-tree[J]. Journal of Beijing University of Aeronautics and Astronautics, 2011, 37(5): 564-568. (in Chinese) |
[1] Beringer J,Hullermeier E.Online clustering of parallel data streams[J].Data & Knowledge Engineering,2006,58(2):180- 204 [2] Li H F,Lee S Y.Mining frequent itemsets over data streams using efficient window sliding techniques [J].Expert Systems with Applications,2009,36(2):1466-1477 [3] Chang J H,Lee W S.Online data stream mining of recent frequent itemsets by sliding window method[J].Journal of Information Science,2005,31(2):76-90 [4] Yu J X,Chong Z H,Lu H J,et al.A false negative approach to mining frequent itemsets from high speed transactional data streams[J].Information Sciences,2006,176 (14):1986-2015 [5] Yang C,Fayyad U,Bradley P S.Efficient discovery of error-tolerant frequent itemsets in high dimensions //Proc of 2001 ACM Int Conf on Knowledge Discovery in Databases.San Francisco,CA:Association for Computing Machinery,2001:194-203 [6] Bashir S, Halim Z,Baig A R.Mining fault tolerant frequent patterns using pattern growth approach //AICCSA 08-6th IEEE/ACS International Conference on Computer Systems and Applications.Doha,Qatar:Inst of Elec and Elec Eng Computer Society,2008:172-179 [7] Zhang S C,Zhang J L,Zhang C Q.EDUA:an efficient algorithm for dynamic database mining[J].Information Sciences,2007,177(13):2756-2767 [8] Chi Y,Wang H,Yu P S,et al.Catch the moment:maintaining closed frequent itemsets over a data stream sliding window[J].Knowledge and Information Systems,2006,10(3):265-294
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