{"id":"W2552308941","doi":"10.3934/bdia.2016008","title":"Time aware topic based recommender system","year":2016,"lang":"en","type":"article","venue":"Big Data and Information Analytics","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Recommender system; Computer science; Collaborative filtering; Information retrieval; Filter (signal processing); Cold start (automotive); World Wide Web; Topic model","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":[0.001487762,0.001058963,0.002098077,0.001788042,0.001298537,0.002104732,0.002173365,0.001997562,0.004791426],"category_scores_gemma":[0.004233328,0.0005573066,0.001519889,0.002255265,0.0002986532,0.002612927,0.0009254276,0.001509554,0.005290925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005819452,"about_ca_system_score_gemma":0.001295064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01203852,"about_ca_topic_score_gemma":0.01348846,"domain_scores_codex":[0.998431,0.0003223564,0.0001389201,0.0004771121,0.0004791554,0.0001513785],"domain_scores_gemma":[0.9972536,0.0008513284,0.0002107621,0.0003695511,0.001180159,0.0001346633],"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":[0.0009919099,0.0006446167,0.01646966,0.001267001,0.001055771,0.001169133,0.001033508,0.1324795,0.04632504,0.02011331,0.05979298,0.7186575],"study_design_scores_gemma":[0.0001539314,0.0003436626,0.00433452,0.0000728306,0.0007222425,0.001321928,0.0002709236,0.9173769,0.009583982,0.00997843,0.0556422,0.000198504],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03866088,0.007343638,0.9296558,0.001301519,0.0009607081,0.0004593286,0.001922166,0.00466315,0.01503283],"genre_scores_gemma":[0.5819437,0.008769489,0.3606582,0.0007512352,0.001378155,0.0006762294,0.0047285,0.0003195735,0.04077493],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01203852,"threshold_uncertainty_score":0.02393693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0647731355806819,"score_gpt":0.2560971786824018,"score_spread":0.1913240431017199,"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."}}