{"id":"W2103800269","doi":"10.1145/1982185.1982417","title":"Mining uncertain web log sequences with access history probabilities","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Traverse; Session (web analytics); Path (computing); A priori and a posteriori; Suffix; Data mining; Web mining; Theoretical computer science; Web page; Algorithm; World Wide Web; Computer network","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":[0.001649825,0.0008365924,0.001152786,0.003084531,0.0005185395,0.001296662,0.001388616,0.0007305288,0.0006732813],"category_scores_gemma":[0.01514359,0.0007598852,0.0008707382,0.003128171,0.0005306607,0.004263991,0.001133174,0.0009476286,0.0003314318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005062299,"about_ca_system_score_gemma":0.0009841354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002427516,"about_ca_topic_score_gemma":0.00336525,"domain_scores_codex":[0.9977704,0.0003862777,0.0002903296,0.0005875506,0.0008350146,0.0001304847],"domain_scores_gemma":[0.9884552,0.007734256,0.001714725,0.00102948,0.0008433721,0.0002230883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001029137,0.0003454428,0.1128625,0.0006267767,0.0003512115,0.002536674,0.0008053654,0.5014226,0.0139527,0.01671909,0.002325454,0.3470231],"study_design_scores_gemma":[0.00001184367,0.00006436942,0.003793988,0.00002274495,0.00003757454,0.000456406,0.00009467162,0.9725911,0.003758872,0.01801392,0.001133768,0.00002072085],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.208661,0.0005852947,0.7865611,0.0002624296,0.00002388491,0.0001341494,0.001624502,0.001309031,0.0008386495],"genre_scores_gemma":[0.8389689,0.0003561697,0.1572898,0.00007178886,0.00005980043,0.0001340597,0.002451556,0.00006410562,0.0006040163],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003084531,"threshold_uncertainty_score":0.008725226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.105357754713933,"score_gpt":0.2688354839739381,"score_spread":0.163477729260005,"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."}}