{"id":"W4308605908","doi":"10.1145/3570500","title":"Modeling User Reviews through Bayesian Graph Attention Networks for Recommendation","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Information Systems","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Huawei Technologies (Canada)","funders":"","keywords":"Computer science; Inference; Semantics (computer science); Graph; Recommender system; Bayesian network; User modeling; Machine learning; Theoretical computer science; Information retrieval; Artificial intelligence; User interface","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":[0.001520007,0.001654104,0.001290564,0.002564132,0.0005917727,0.00119905,0.001917238,0.001824768,0.002578266],"category_scores_gemma":[0.01004632,0.001044387,0.001363027,0.002643929,0.0004925763,0.002946344,0.0006552793,0.002327775,0.001382084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002169028,"about_ca_system_score_gemma":0.00104699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0633875,"about_ca_topic_score_gemma":0.08895086,"domain_scores_codex":[0.9986779,0.0005062457,0.00005886492,0.0004086684,0.0002560565,0.0000922281],"domain_scores_gemma":[0.9964462,0.002289697,0.0002944471,0.0002733971,0.0006082425,0.00008790485],"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":[0.0003148036,0.0001845087,0.007096168,0.0002796164,0.0003610081,0.0001259596,0.0002244025,0.7774041,0.001838884,0.01785294,0.01358801,0.1807295],"study_design_scores_gemma":[0.000005969437,0.00001205984,0.0005399071,0.000009135193,0.00002904133,0.00001391884,0.000004822593,0.9916658,0.0001151759,0.006837577,0.0007592528,0.000007322778],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04443741,0.004708399,0.9401145,0.001353163,0.0002196407,0.0001821957,0.0015002,0.002424969,0.005059515],"genre_scores_gemma":[0.8016312,0.003087704,0.1788578,0.0009722941,0.0005142285,0.0003301137,0.003956928,0.0002401152,0.01040958],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0633875,"threshold_uncertainty_score":0.1260371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0458326038559435,"score_gpt":0.2828956684031741,"score_spread":0.2370630645472306,"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."}}