Summarizing and mining streaming data via a functional data approach

Studies in Classification, Data Analysis, and Knowledge Organization

Volumn , Issue , 2011, Pages 409-416

  Balzanella, Antonio ^a   Romano, Elvira ^b   Verde, Rosanna ^b  

^a UNIVERSITY OF NAPLES FEDERICO II   (Italy)

^b NONE

Author keywords

[No Author keywords available]

Indexed keywords

ANALYSIS OF DATA; CLUSTERING STRATEGY; DIVIDE AND CONQUER; FUNCTIONAL DATAS; SAMPLING PROBLEMS; STATISTICAL INFORMATION; STREAMING DATA; TRADITIONAL TECHNIQUES;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 84888226254     PISSN: 14318814     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-642-13312-1_43     Document Type: Conference Paper

References (6)

1. Abrham, C., Corillon, P.A., Matzner-Löber, E., Molinari, N.: Unsupervised curves clustering using b-splines. Scand. J. Stat. 30(3), 581-595 (2003)
2. Aggarwal, C., Han, J., Wang, J., Yu, P.: A framework for clustering evolving data streams. In: VLDB Conference, Berlin, Germany (2003)
3. De Boor, C.: A Practical Guide to Splines. Springer, New York, NY (1978)
4. Pseudo Periodic Synthetic Time Series. In: The UCI KDD Archive Information and Computer Science University of California, Irvine. http://kdd.ics.uci.edu/. Cited 10 Dec 2008
5. Ramsay, J.O., Silverma, B.W.: Functional Data Analysis, 2nd edn. Springer, New York, NY (2005)
6. Tang, L.A., Cui, B., Li, H.Y., Miao, G.S., Yang, D.Q., Zhou, X.B.: PGG: an online pattern based approach for stream variation mnagement. J. Comput. Sci. Technol. 23(4), 497-515 (2008)