Discovering temporal knowledge in multivariate time series

Studies in Classification, Data Analysis, and Knowledge Organization

Volumn , Issue , 2005, Pages 272-279

  Mörchen, Fabian ^a   Ultsch, Alfred ^a  

^a PHILIPPS UNIVERSITY MARBURG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

TIME SERIES;

BOTTOM-UP MANNER; DATA MINING ALGORITHM; MULTIVARIATE TIME SERIES; MUSCLE ACTIVITIES; TEMPORAL CONCEPTS; TEMPORAL KNOWLEDGE; TEMPORAL PATTERN; TIME SERIES KNOWLEDGE MININGS;

DATA MINING;

EID: 84879520297     PISSN: 14318814     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/3-540-28084-7_30     Document Type: Conference Paper

References (17)

1. ALLEN, J. F. (1983): Maintaining knowledge about temporal intervals. Comm. ACM, 26(11), 832-843.
2. GUIMARAES, G. and ULTSCH, A. (1999): A method for temporal knowledge conversion. In: D. J. Hand, J. N. Kok and M. R. Berthold (Eds.): Proc. of the 3rd Int. Symp. on Advances in Intelligent Data Analysis. Amsterdam, Springer, 369-380.
3. HETLAND, M. L. (2004): A survey of recent methods for efficient retrieval of similar time sequences. In: M. Last, A. Kandel and H. Bunke (Eds.): Data Mining in Time Series Databases. World Scientific, 23-42.
4. HETLAND, M. L. and SAETROM, P. (2002): Temporal rule discovery using genetic programming and specialized hardware. In: A. Lotfi, J. Garibaldi, and R. John (Eds.): Proc. of the 4th Int. Conf. on Recent Advances in Soft Computing (RASC), 182-188.
5. HÖPPNER, F. (2001): Discovery of temporal patterns - learning rules about the qualitative behaviour of time series. In: Proc. of the 5th European PKDD. Springer, Berlin, 192-203.
6. HÖPPNER, F. (2002): Learning dependencies in multivariate time series. Proc. of the ECAI'02 Workshop on Knowledge Discovery in (Spatio-) Temporal Data, Lyon, France, 25-31.
7. KADOUS, M. W. (1999): Learning comprehensible descriptions of multivariate time series. In: Proc. 16th International Conf. on Machine Learning, 454-463.
8. LAST, M., KLEIN, Y. and KANDEL, A. (2001): Knowledge discovery in time series databases. IEEE Transactions on Systems, Man, and Cybernetics (31B).
9. LIN, J., KEOGH, E., LONARDI, S. and CHIU, B. (2003): A symbolic representation of time series, with implications for streaming algorithms. In: Proc. 8th ACM SIGMOD workshop DMKD 2003, 2-11.
10. POVINELLI, R. J. (2000): Identifying temporal patterns for characterization and prediction of financial time series events. In: Proc. International Workshop on Temporal, Spatial and Spatio-Temporal Data Mining: TSDM 2000, Lyon, France, 46-61.
11. SAETROM, P. and HETLAND, M. L. (2003): Unsupervised temporal rule mining with genetic programming and specialized hardware. In: Proc. Int. Conf. on Machine Learning and Applications, ICMLA, 145-151.
12. ULTSCH, A. (1991): Konnektionistische Modelle und ihre Integration mit wissensbasierten Systemen. Forschungsbericht Informatik Nr. 396, Universität Dortmund, Habilitationsschrift.
13. ULTSCH, A. (1996): Eine unifikationsbasierte Grammatik zur Beschreibung von komplexen Mustern in multivariaten Zeitreihen. personal communication
14. ULTSCH, A. (1999): Data Mining and Knowledge Discovery with Emergent Self-Organizing Feature Maps for Multivariate Time Series. In: Oja, E. and Kaski, S. (Eds.): Kohonen Maps, Elsevier, New York, 33-46.
15. ULTSCH, A. (2004): Unification-based temporal grammar. Technical Report No. 37, Philipps-University Marburg, Germany.
16. VILO, J. (1998): Discovering frequent patterns from strings. Technical Report C-1998-9, Department of Computer Science, University of Helsinki.
17. YANG, J., WANG, W., YU, P.S. and HAN, J. (2002): Mining long sequential patterns in a noisy environment. In: Proceedings of the 2002 ACM SIGMOD international conference on Management of data, 406-417.