{"id":"W4248822770","doi":"10.1109/ideas.2004.1319823","title":"Incremental mining of Web sequential patterns using PLWAP tree on tolerance MinSupport","year":2004,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Tree (set theory); Data mining; Database; Fractal tree index; Tree structure; Data structure; Incremental decision tree; Decision tree; Decision tree learning; Programming language; Mathematics","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":[0.001108572,0.0005637333,0.001029642,0.00344253,0.0007200416,0.001202209,0.002042548,0.0006825299,0.001055945],"category_scores_gemma":[0.008929199,0.0005983259,0.0008697879,0.00349147,0.0004102004,0.00317147,0.001355313,0.0008739521,0.0006227962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003860108,"about_ca_system_score_gemma":0.001201865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003101299,"about_ca_topic_score_gemma":0.004834576,"domain_scores_codex":[0.9984637,0.0002233961,0.0001765068,0.0002997767,0.0007018713,0.0001347005],"domain_scores_gemma":[0.9962505,0.001722076,0.0004543332,0.0006286913,0.0007700353,0.0001743054],"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":[0.0005812193,0.0002714251,0.01991726,0.000374161,0.0001608953,0.0007984343,0.0005084708,0.06213174,0.01680341,0.006181949,0.006736504,0.8855345],"study_design_scores_gemma":[0.00007007049,0.0002446662,0.003506356,0.00005554308,0.00008711404,0.001037607,0.0002461683,0.9528925,0.01448294,0.01861963,0.008717163,0.00004016617],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1262429,0.0006630653,0.8646705,0.0003725963,0.00006691295,0.0004850992,0.001450659,0.004541907,0.001506391],"genre_scores_gemma":[0.2689883,0.00023227,0.7261099,0.0001316581,0.00005289119,0.0003353801,0.002979035,0.0001628952,0.001007646],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00344253,"threshold_uncertainty_score":0.006166458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03985169507216933,"score_gpt":0.2870730358012076,"score_spread":0.2472213407290383,"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."}}