{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003490631,0.00008493686,0.0001160302,0.0001271376,0.00007434501,0.0002005746,0.000641672,0.0000519533,0.0000111956],"category_scores_gemma":[0.00002275679,0.00005391842,0.00001812631,0.0001385405,0.00001584838,0.002956849,0.0003153659,0.0000336712,0.000115363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003595213,"about_ca_system_score_gemma":0.00004241004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001112501,"about_ca_topic_score_gemma":0.000001910204,"domain_scores_codex":[0.9992737,0.00003023404,0.0002991748,0.0001301898,0.000143901,0.000122764],"domain_scores_gemma":[0.998811,0.00004796619,0.0001262347,0.0008798708,0.00006759856,0.0000673024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002652101,0.00001430025,0.0005141677,0.000131421,0.00002831683,0.000001602326,0.0001281274,0.00000139895,0.00001393732,0.02991506,0.1604397,0.8088093],"study_design_scores_gemma":[0.0002704739,0.00002604815,0.000241126,0.00008001726,0.000005427577,0.00001065474,0.00004068967,0.3544524,0.000104181,0.0000538474,0.6445938,0.0001213304],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00008612937,0.00001282708,0.9905476,0.003077833,0.0002233697,0.00009639592,0.00008061836,0.0002176295,0.005657594],"genre_scores_gemma":[0.9825485,0.00008733571,0.01406297,0.002379048,0.000147051,0.00001082413,0.0002364494,0.000006908437,0.000520909],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9824624,"threshold_uncertainty_score":0.219873,"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."}}