{"id":"W2157169143","doi":"10.1109/icdm.2012.20","title":"Direct Discovery of High Utility Itemsets without Candidate Generation","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":179,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Simon Fraser University","funders":"","keywords":"Computer science; Scalability; Data mining; Pruning; Bounding overwatch; Property (philosophy); Artificial intelligence; Database","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002225165,0.00005991521,0.00009287846,0.00002572109,0.00005675435,0.00006845807,0.0002722999,0.00002045782,0.00001296814],"category_scores_gemma":[0.00001265356,0.0000468604,0.00002047958,0.0001504772,0.0000235671,0.001077033,0.000118464,0.00002823676,0.00001819308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009568947,"about_ca_system_score_gemma":0.00002322608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006963382,"about_ca_topic_score_gemma":0.00004213599,"domain_scores_codex":[0.9994182,0.00002305404,0.0001374225,0.0001605999,0.0001192453,0.0001414806],"domain_scores_gemma":[0.999355,0.00002221284,0.00005611821,0.000488514,0.00002871248,0.00004941153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000007291641,0.0008860023,0.07445814,0.00003970313,0.00007601248,8.286646e-7,0.001620925,0.00004264743,0.04370318,0.4524613,0.0388049,0.3878991],"study_design_scores_gemma":[0.0005814257,0.00008388377,0.2181252,0.00002306688,0.00003296832,0.00001315661,0.0000440762,0.3321343,0.4119141,0.0008504199,0.03558371,0.0006136509],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2405016,0.00004634453,0.7553432,0.0001752586,0.0002135303,0.00007398323,0.00004541799,0.00005911051,0.003541578],"genre_scores_gemma":[0.9264166,0.000006570171,0.07272169,0.00005985998,0.0000961614,0.00001308221,0.00003883131,0.000002742902,0.0006444645],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.685915,"threshold_uncertainty_score":0.1910912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02712208151631306,"score_gpt":0.2701453798814657,"score_spread":0.2430232983651526,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}