Large-scale graph mining using backbone refinement classes

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2009, Pages 617-625

  Maunz, Andreas ^a   Helma, Christoph ^b   Kramer, Stefan ^c  

^a UNIVERSITY OF FREIBURG   (Germany)

^b In Silico Toxicology   (Switzerland)

^c TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

Experimentation; Performance; Theory

Indexed keywords

CLASS SIZE; CLASSIFICATION ACCURACY; CLOSED FRAGMENTS; CROSS VALIDATION; DATA SETS; DESCRIPTORS; EXPERIMENTATION; FEATURE ENTROPY; FEATURE SETS; GRAPH MINING; LARGE PARTS; LARGE-SCALE DATASETS; NEW APPROACHES; PERFORMANCE; RUNNING TIME; SEARCH SPACES; STATISTICAL CONSTRAINTS; SUBGRAPHS; THEORY; TRAINING SETS; TREE MINING; UPPER BOUND;

EXPERIMENTS; TEACHING;

MINING;

EID: 70350627641     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1557019.1557089     Document Type: Conference Paper

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