{"id":"W1978384613","doi":"10.1145/1651587.1651595","title":"A session generalization technique for improved web usage mining","year":2009,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Generalization; Computer science; Session (web analytics); Scalability; Hierarchy; Set (abstract data type); Sample (material); Data mining; Quality (philosophy); Theoretical computer science; Information retrieval; Machine learning; World Wide Web; Database; Mathematics; Programming language","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":[],"consensus_categories":[],"category_scores_codex":[0.0003166269,0.00009432531,0.0001142281,0.00009086876,0.00009268989,0.0001243118,0.0003398036,0.00007460685,0.000004453967],"category_scores_gemma":[0.00001171448,0.00007400977,0.00005006019,0.0001787251,0.000003864143,0.0003610787,0.00004872368,0.00003270768,8.969734e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002598093,"about_ca_system_score_gemma":0.00003028413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001045738,"about_ca_topic_score_gemma":0.000004344807,"domain_scores_codex":[0.9992991,0.00002905195,0.0001920299,0.0002478649,0.00006498605,0.0001669639],"domain_scores_gemma":[0.9994957,0.00002240431,0.00007388829,0.0003078808,0.00005789719,0.00004217581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000003707712,0.00006154674,0.00006916399,0.00001644982,0.000005021514,0.000001148469,0.0001677269,0.00000276028,0.6804829,0.1100414,0.03495425,0.174194],"study_design_scores_gemma":[0.0004593367,0.0005498675,0.000192983,0.00008064798,0.000004019757,0.00002993166,0.00001618979,0.3279844,0.5747517,0.01900594,0.07652339,0.0004015835],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004146628,0.00002362479,0.9922228,0.001497775,0.0001156815,0.0006081431,8.250184e-7,0.0005469407,0.004569522],"genre_scores_gemma":[0.3164722,0.000008668861,0.6817378,0.0008789628,0.00005773686,0.0001199629,0.000003424692,0.000005385782,0.0007158862],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3279816,"threshold_uncertainty_score":0.3018031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0232101134049451,"score_gpt":0.2839753354645008,"score_spread":0.2607652220595557,"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."}}