{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002620087,0.00113069,0.001669747,0.002007708,0.001153349,0.003921469,0.001934597,0.00226423,0.00532089],"category_scores_gemma":[0.01049151,0.0009520208,0.001044826,0.003094662,0.0008691343,0.005619796,0.00174866,0.003448378,0.002983328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001592549,"about_ca_system_score_gemma":0.001471442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008348251,"about_ca_topic_score_gemma":0.008955954,"domain_scores_codex":[0.9980895,0.0005130749,0.0001711894,0.0003949624,0.0006981818,0.0001331077],"domain_scores_gemma":[0.9949889,0.002326526,0.0002558494,0.00112856,0.001028857,0.0002713547],"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":[0.0008660841,0.0005661085,0.01355455,0.001064913,0.0006359174,0.0007077291,0.0005830763,0.2079028,0.01129951,0.1066506,0.08635953,0.5698091],"study_design_scores_gemma":[0.00005539782,0.00008402117,0.001826611,0.0001398504,0.00008355819,0.0001614679,0.0002889792,0.7843177,0.004745927,0.1741259,0.03410715,0.00006349937],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01629032,0.007869341,0.9420642,0.0105878,0.0008261187,0.0004105806,0.003106414,0.008019486,0.01082573],"genre_scores_gemma":[0.4914418,0.008103539,0.4827953,0.002341385,0.001108252,0.0005503225,0.005382444,0.000531801,0.007745215],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008348251,"threshold_uncertainty_score":0.01780009,"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."}}