{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005904639,0.002009987,0.002254194,0.01127989,0.001123441,0.004337171,0.004012777,0.002146513,0.003380337],"category_scores_gemma":[0.01569924,0.0009610943,0.00175648,0.01993494,0.001280025,0.008406404,0.001347549,0.002531636,0.004808785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001550476,"about_ca_system_score_gemma":0.00377114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002244065,"about_ca_topic_score_gemma":0.001684907,"domain_scores_codex":[0.9944044,0.001118697,0.0009690289,0.001020817,0.002322363,0.0001645939],"domain_scores_gemma":[0.9894288,0.005581796,0.0005956767,0.0007946815,0.003428592,0.0001704738],"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":[0.00006199003,0.000150519,0.002503383,0.003979444,0.0001368254,0.0001965273,0.0002445334,0.007004847,0.001119951,0.07572141,0.0167041,0.8921766],"study_design_scores_gemma":[0.00008593519,0.0004653084,0.003154749,0.004073422,0.0002493643,0.004602333,0.0004663457,0.1040231,0.004623978,0.3354673,0.5425833,0.0002047006],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.003680165,0.1911608,0.7796493,0.004159501,0.0009110859,0.000892119,0.001177805,0.001440661,0.01692847],"genre_scores_gemma":[0.02225502,0.1663861,0.8009118,0.001076167,0.001027957,0.0009242094,0.002398322,0.0001531492,0.004867184],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01127989,"threshold_uncertainty_score":0.03122711,"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."}}