{"id":"W3119545471","doi":"10.1609/aaai.v35i5.16553","title":"Knowledge-Enhanced Top-K Recommendation in Poincaré Ball","year":2021,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Interpretability; Computer science; Recommender system; Knowledge graph; Learning to rank; Graph; Regularization (linguistics); Artificial intelligence; Machine learning; Information retrieval; Theoretical computer science; Ranking (information retrieval)","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":[0.00195065,0.0007224786,0.00254456,0.001710097,0.001063499,0.001796353,0.003502958,0.001803718,0.006237557],"category_scores_gemma":[0.007334649,0.0007533923,0.001296223,0.003051942,0.001526274,0.002797516,0.001695787,0.001369054,0.002452699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001942046,"about_ca_system_score_gemma":0.001825918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05936041,"about_ca_topic_score_gemma":0.03136255,"domain_scores_codex":[0.9983323,0.0005882966,0.00009690074,0.0003762519,0.0004529736,0.0001532866],"domain_scores_gemma":[0.996646,0.001713862,0.0002126843,0.000547727,0.0007204492,0.0001592909],"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":[0.0004452493,0.0002126161,0.002384889,0.0002278257,0.0001413443,0.0002555201,0.0002107701,0.7984366,0.001412409,0.0592303,0.01071544,0.126327],"study_design_scores_gemma":[0.00001473717,0.00002296681,0.0001715738,0.000007100517,0.000007521895,0.00001982249,0.0000082304,0.986534,0.0001649202,0.01235562,0.0006845557,0.000009059537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05505203,0.00230121,0.928969,0.0009721557,0.0002018542,0.000139877,0.0005179591,0.001303353,0.01054257],"genre_scores_gemma":[0.7833177,0.001851397,0.1954261,0.000838098,0.0003243892,0.0002332327,0.001729883,0.0001869139,0.01609221],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05936041,"threshold_uncertainty_score":0.1180298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08167864707999131,"score_gpt":0.3210844721252952,"score_spread":0.2394058250453039,"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."}}