{"id":"W1995221706","doi":"10.5539/cis.v6n4p88","title":"Data Mining Techniques and Preference Learning in Recommender Systems","year":2013,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Recommender system; Computer science; Component (thermodynamics); Preference; Set (abstract data type); Association rule learning; Order (exchange); Preference learning; Information retrieval; World Wide Web; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0006947026,0.00006992646,0.00007885056,0.0002185785,0.0002089161,0.001424501,0.0009720285,0.0000221297,0.000001322603],"category_scores_gemma":[0.00002596849,0.0000603786,0.000003085702,0.0005295817,0.0001083075,0.01755309,0.001287014,0.00009029934,0.00001277777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001324949,"about_ca_system_score_gemma":0.00004826954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006171166,"about_ca_topic_score_gemma":6.561324e-7,"domain_scores_codex":[0.9991733,0.00001694911,0.0002304178,0.0002441124,0.0001689603,0.0001662741],"domain_scores_gemma":[0.9992706,0.0000566771,0.00008241007,0.0004248828,0.00009048206,0.00007497852],"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":[1.25239e-7,0.000004106033,0.0006826128,0.00001067549,5.528031e-7,9.753985e-8,0.0008852007,0.00001960569,0.00001351021,0.006738482,0.0008269054,0.9908181],"study_design_scores_gemma":[0.00007122953,0.0000260288,0.01029341,0.00003681592,3.831509e-7,0.00002272474,0.0001326978,0.9576572,0.0000248028,0.00006778004,0.03157761,0.00008930336],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02358883,0.00005803823,0.9721396,0.0006055839,0.0001255852,0.0002501621,0.000005668876,0.0001594024,0.003067165],"genre_scores_gemma":[0.4397254,0.0002009451,0.5595246,0.0003916132,0.00004313244,0.00005650383,0.00002783641,0.000002522764,0.00002743702],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9907288,"threshold_uncertainty_score":0.9996121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06092787821162245,"score_gpt":0.2794478995151464,"score_spread":0.2185200213035239,"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."}}