{"id":"W2146606092","doi":"10.1145/1824795.1824798","title":"A taxonomy of sequential pattern mining algorithms","year":2010,"lang":"en","type":"review","venue":"ACM Computing Surveys","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":396,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Taxonomy (biology); Tree traversal; Sequential Pattern Mining; Key (lock); Data mining; Web mining; Information retrieval; Artificial intelligence; Machine learning; Algorithm; Web page; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003191373,0.0005059811,0.001515579,0.0002769301,0.0001974817,0.0002758596,0.005267059,0.0003468246,0.0000123382],"category_scores_gemma":[0.0002886992,0.0004682482,0.0004283673,0.0008707221,0.0001099576,0.0002051736,0.002876463,0.0007144632,0.000082934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000433679,"about_ca_system_score_gemma":0.0004148738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002272038,"about_ca_topic_score_gemma":0.00001566942,"domain_scores_codex":[0.9962771,0.000736769,0.001100014,0.001001511,0.0003713996,0.0005132255],"domain_scores_gemma":[0.9943764,0.00133255,0.001088381,0.002891943,0.0001638532,0.0001469018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[3.112144e-8,0.00004207279,0.00001856594,0.0007663678,0.0000557677,0.00000747183,0.00005502376,0.00000129478,2.936022e-7,0.00009756508,0.0004192403,0.9985363],"study_design_scores_gemma":[0.0001182162,0.00003437724,0.00005077722,0.002763454,0.00009592209,0.00007796565,0.000004966478,0.01364663,0.000003324913,0.00003346361,0.9826189,0.0005519706],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000005728662,0.3728141,0.6255513,0.000015589,0.0008115123,0.0003799033,0.0001073084,0.0001587113,0.0001558752],"genre_scores_gemma":[0.00003314732,0.4229795,0.5757232,0.00002685139,0.0006203607,0.00009251416,0.0003684454,0.00006701465,0.00008893301],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9979843,"threshold_uncertainty_score":0.9997769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1231731861239806,"score_gpt":0.3469654630301945,"score_spread":0.2237922769062139,"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."}}