{"id":"W2982365687","doi":"10.1109/dasc/picom/cbdcom/cyberscitech.2019.00190","title":"Big Data Analytics for Personalized Recommendation Systems","year":2019,"lang":"en","type":"article","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Big data; Computer science; Recommender system; Data science; Analytics; Exploit; Variety (cybernetics); Hidden Markov model; Focus (optics); Personalization; World Wide Web; Data mining; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003422803,0.00005336465,0.00009262106,0.00003635074,0.00005301476,0.0002257525,0.000647301,0.00002359481,0.00004069078],"category_scores_gemma":[0.00002140195,0.00004260287,0.00001729641,0.0001335902,0.000006726071,0.0004386851,0.0001925098,0.00002774117,0.00005789901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000141303,"about_ca_system_score_gemma":0.00005290875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001483532,"about_ca_topic_score_gemma":0.000001954596,"domain_scores_codex":[0.9993899,0.0000141099,0.0001191026,0.0002712875,0.00008722173,0.0001183176],"domain_scores_gemma":[0.9992902,0.00006766065,0.00006445288,0.0004953599,0.0000532361,0.00002909508],"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":[0.00001090273,0.00005547308,0.0009287342,0.0003038252,0.00005482152,5.873328e-7,0.0004187439,0.0001187248,0.0008760003,0.1775866,0.1791449,0.6405007],"study_design_scores_gemma":[0.0002377537,0.00001321014,0.00001839711,0.00001294024,0.000003526469,0.00000189381,0.00004560919,0.6448441,0.00006161071,0.0002245022,0.3544693,0.00006720141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004589526,0.0000422641,0.9876704,0.00219933,0.00098277,0.0001567603,0.00000728532,0.00006912893,0.008413065],"genre_scores_gemma":[0.7236717,0.0000243316,0.2126841,0.005188266,0.0008818745,0.00002317369,0.0003500711,0.00002316778,0.05715329],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7749863,"threshold_uncertainty_score":0.2176937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1823697858825858,"score_gpt":0.3139077062164156,"score_spread":0.1315379203338297,"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."}}