{"id":"W4200289216","doi":"10.1109/bigdia53151.2021.9619632","title":"An Explainable TV Program Recommendation Model Based on Attention Mechanisms","year":2021,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Interpretability; Computer science; Process (computing); Recommender system; Artificial neural network; Machine learning; Artificial intelligence; Attention network; Data science; Information retrieval; Multimedia","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":[0.0009704142,0.0007425153,0.0007370629,0.001111266,0.0004927968,0.001101066,0.001857708,0.002239604,0.004805842],"category_scores_gemma":[0.004353587,0.0004499453,0.001107879,0.0009343731,0.000635451,0.001808498,0.0005944003,0.001990118,0.0008899129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001372397,"about_ca_system_score_gemma":0.0009392944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03020512,"about_ca_topic_score_gemma":0.0295085,"domain_scores_codex":[0.9994718,0.0001323923,0.00002656476,0.0002111036,0.00008304762,0.00007501419],"domain_scores_gemma":[0.9984211,0.0009765507,0.0001488594,0.0001038607,0.0002863959,0.00006326094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004500239,0.0003565854,0.009274175,0.000254695,0.0002894433,0.0005787858,0.0008034742,0.7488143,0.008960154,0.08569822,0.009468571,0.1350514],"study_design_scores_gemma":[0.00002203564,0.00002907559,0.0007219636,0.000008563099,0.00004167,0.00003712716,0.00001185596,0.9896159,0.0002818999,0.008647962,0.0005696203,0.00001232944],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.136072,0.0009146091,0.8443343,0.004438024,0.0002058257,0.0001989877,0.001383618,0.001939242,0.0105134],"genre_scores_gemma":[0.8897585,0.0005757486,0.08984234,0.0005569814,0.000169452,0.0003400049,0.0008893685,0.000094966,0.01777253],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03020512,"threshold_uncertainty_score":0.06005865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0292286842024865,"score_gpt":0.2955930316485024,"score_spread":0.2663643474460159,"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."}}