{"id":"W2912803559","doi":"10.1109/bigdata.2018.8622063","title":"Towards a New Approach to Empower Periodic Pattern Mining for Massive Data using Map-Reduce","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Timestamp; Data mining; Pruning; Time series; Suffix tree; Big data; Data structure; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001351828,0.0009046148,0.001304975,0.002181238,0.001152046,0.001917392,0.00309693,0.0006595298,0.001480995],"category_scores_gemma":[0.002863826,0.0006942817,0.001495439,0.003176188,0.0006549016,0.003094322,0.002247409,0.001262791,0.001259703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005389464,"about_ca_system_score_gemma":0.001943494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005407326,"about_ca_topic_score_gemma":0.00772412,"domain_scores_codex":[0.9984366,0.0002084593,0.0001166213,0.0003500941,0.0007723855,0.0001157914],"domain_scores_gemma":[0.9986634,0.000227825,0.00007886241,0.0004943697,0.0004448387,0.00009067646],"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":[0.0005200596,0.000875416,0.007721472,0.0008569744,0.0005786947,0.0008898975,0.0008492117,0.07915943,0.03640551,0.05928982,0.03885254,0.7740008],"study_design_scores_gemma":[0.00007751728,0.000167651,0.001840839,0.00003127621,0.0001061918,0.0007164889,0.000357868,0.8573177,0.01772491,0.07784791,0.04375326,0.0000584166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008313541,0.0004516633,0.9855488,0.0005462207,0.0001086832,0.0001318967,0.0003118547,0.003262046,0.001325311],"genre_scores_gemma":[0.07601646,0.0005045095,0.9194819,0.000221817,0.0001307381,0.0001697316,0.001298484,0.0002574357,0.001918904],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005407326,"threshold_uncertainty_score":0.01075172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1412377093483993,"score_gpt":0.3587301333366876,"score_spread":0.2174924239882883,"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."}}