Hypergraph-based anomaly detection of high-dimensional co-occurrences

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 31, Issue 3, 2009, Pages 563-569

  Silva, Jorge ^a   Willett, Rebecca ^a  

^a Duke University   (United States)

Author keywords

Anomaly detection; Co occurrence analysis; Social networks; Unsupervised learning; Variational methods

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; UNSUPERVISED LEARNING;

ANOMALY DETECTION; CO OCCURRENCES; CO-OCCURRENCE ANALYSIS; DIMENSIONALITY REDUCTIONS; EXPECTATION-MAXIMIZATION ALGORITHMS; FEATURE SELECTIONS; HIGH-DIMENSIONAL; HIGH-DIMENSIONAL PROBLEMS; HYPER GRAPHS; HYPERGRAPH; NOVEL METHODS; REGULARIZATION PARAMETERS; SOCIAL NETWORKS; STATE-OF-THE-ART METHODS; SYNTHETIC DATUM; VARIATIONAL METHODS;

GRAPH THEORY;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER SIMULATION; METHODOLOGY; THEORETICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; MODELS, THEORETICAL; PATTERN RECOGNITION, AUTOMATED;

EID: 59549090927     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2008.232     Document Type: Article

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