Analysis of time series using compact model-based descriptions

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4947 LNCS, Issue , 2008, Pages 698-701

  Kriegel, Hans Peter ^a   Kröger, Peer ^a   Pryakhin, Alexey ^a   Renz, Matthias ^a  

^a UNIVERSITY OF MUNICH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ADVANCED APPLICATIONS; COMPACT MODELING; COMPRESSION METHODS; DATA MINING TASKS; HEIDELBERG (CO); INTERNATIONAL CONFERENCES; MODEL BASED (OPC); NOVEL METHODS; REFERENCE TIME; TIME SERIES;

DATA COMPRESSION; DATABASE SYSTEMS; DECISION SUPPORT SYSTEMS; INFORMATION MANAGEMENT; KNOWLEDGE MANAGEMENT; MATHEMATICAL MODELS; SEARCH ENGINES;

TIME SERIES ANALYSIS;

EID: 47249115224     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-78568-2_66     Document Type: Conference Paper

References (4)

1. Faloutsos, C., Ranganathan, M., Maolopoulos, Y.: Fast Subsequence Matching in Time-series Databases. In: Proc. SIGMOD Conference (1994)
2. Ratanamahatana, C.A., Keogh, E., Bagnall, A.J., Lonardi, S.: A Novel Bit Level Time Series Representation with Implication for Similarity Search and Clustering. In: Ho, T.-B., Cheung, D., Liu, H. (eds.) PAKDD 2005. LNCS (LNAI), vol. 3518, Springer, Heidelberg (2005)
3. Kriegel, H.-P.: Approximate Clustering of Time Series Using Compact Model-based Descriptions. In: Haritsa, et al. (eds.) DASFAA 2008. LNCS, vol. 4947. Springer, Heidelberg (to appear, 2008)
4. Ankerst, M., Breunig, M.M., Kriegel, H.P., Sander, J.: OPTICS: Ordering Points to Identify the Clustering Structure. In: Proc. SIGMOD Conference (1999)