HOT aSAX: A novel adaptive symbolic representation for time series discords discovery

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

Volumn 5990 LNAI, Issue PART 1, 2010, Pages 113-121

  Pham, Ninh D ^a   Le, Quang Loc ^a   Dang, Tran Khanh ^a  

^a VIETNAM NATIONAL UNIVERSITY   (Viet Nam)

Author keywords

Anomaly Detection; Clustering; SAX; Time Series Data Mining

Indexed keywords

ANOMALY DETECTION; CLUSTERING; DATA CLEANSING; DATA SETS; EMPIRICAL EXPERIMENTS; FAULT DIAGNOSTICS; FINANCIAL DATA ANALYSIS; K-MEANS; REAL-WORLD; REAL-WORLD APPLICATION; SAX; SYMBOLIC REPRESENTATION; TIME SERIES DATA MINING; TIME SERIES DATABASE;

APPROXIMATION ALGORITHMS; CLUSTER ANALYSIS; DATA MINING; DATABASE SYSTEMS; TIME SERIES;

TIME SERIES ANALYSIS;

EID: 77956986275     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-12145-6_12     Document Type: Conference Paper

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