{"id":"W2584045454","doi":"10.1109/bigdata.2016.7840678","title":"Distributed and parallel high utility sequential pattern mining","year":2016,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada); York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Correctness; Big data; Pruning; Process (computing); Data mining; Distributed memory; Distributed database; Sequence (biology); Distributed Computing Environment; Distributed computing; Parallel computing; Shared memory; Algorithm","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001992547,0.000689558,0.001117787,0.001570137,0.001051176,0.001177255,0.002046846,0.0006197451,0.001061455],"category_scores_gemma":[0.005628981,0.0004509399,0.0008358382,0.002764007,0.0007385454,0.001955141,0.00147462,0.0007661632,0.0003824366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005653581,"about_ca_system_score_gemma":0.001898549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003294025,"about_ca_topic_score_gemma":0.005071501,"domain_scores_codex":[0.9981756,0.0003781515,0.0001529865,0.0005936531,0.0005227447,0.0001768592],"domain_scores_gemma":[0.9968072,0.001207167,0.0002985413,0.0008495515,0.0006594964,0.0001781045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008757708,0.0005257484,0.02267585,0.0004772239,0.0003109607,0.0008772671,0.0004374334,0.3231034,0.01611287,0.02158875,0.009390548,0.6036242],"study_design_scores_gemma":[0.00006555316,0.00008512945,0.001681851,0.000007337557,0.00003163322,0.000324968,0.0001151394,0.9658574,0.004701856,0.02505454,0.002063137,0.00001138648],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09120961,0.0004822511,0.9031941,0.0004415484,0.00007602087,0.0002082206,0.0004303164,0.002133119,0.00182479],"genre_scores_gemma":[0.5660697,0.0002428236,0.4299524,0.0001159826,0.00007350579,0.0002152425,0.001141954,0.00009902706,0.002089432],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003294025,"threshold_uncertainty_score":0.01053774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02436350499762241,"score_gpt":0.2515603025719915,"score_spread":0.2271967975743691,"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."}}