Automatic detection of trends in time-stamped sequences: an evolutionary approach-Reference-Cited by-同舟云学术

Automatic detection of trends in time-stamped sequences: an evolutionary approach

Published:2009-01-14 Issue:3 Volume:14 Page:211-227
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Araujo Lourdes,Merelo Juan Julián

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s00500-008-0395-8.pdf

Reference23 articles.

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3. Araujo L, Cuesta JA, Merelo JJ (2006) Genetic algorithm for burst detection and activity tracking in event streams. In: Runarsson TP, Beyer HG, Burke E, Guervós JJM, Bullinaria LDWA, Rowe J, Yao X (eds) Proceedings PPSN IX, no. 4193. Lecture notes in computer science, LNCS. Springer, Berlin, pp 453–462

4. Bingham E, Kabán A, Girolami M (2003) Topic identification in dynamical text by complexity pursuit. Neural Process Lett 17(1):69–83

5. Charikar M, Chen K, Farach-Colton M (2002) Finding frequent items in data streams. In: Charikar M, Chen K, Farach-Colton M. Finding frequent items in data streams. In: Proceedings of the 29th International Colloquium on Automata, Languages, and Programming, 2002. http://citeseer.ist.psu.edu/charikar02finding.html

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