{"id":"W3102793640","doi":"10.1145/3423322","title":"Neural Feature-aware Recommendation with Signed Hypergraph Convolutional Network","year":2020,"lang":"en","type":"article","venue":"ACM Transactions on Information Systems","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Collaborative filtering; Recommender system; Bridging (networking); Hypergraph; Profiling (computer programming); Feature (linguistics); Convolutional neural network; Embedding; Graph; Information retrieval; Preference; Artificial intelligence; Machine learning; Data mining; Theoretical computer science","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":[0.0004214027,0.000806877,0.0008553353,0.0007961331,0.0003484795,0.0006956119,0.001510551,0.00131274,0.001450373],"category_scores_gemma":[0.002042813,0.0005559328,0.0007143159,0.00130636,0.0004445477,0.00167627,0.0005832143,0.001339435,0.0006159862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001126115,"about_ca_system_score_gemma":0.0007204185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02351565,"about_ca_topic_score_gemma":0.03462221,"domain_scores_codex":[0.99975,0.00006018241,0.00001278474,0.00008233228,0.00005804246,0.00003678288],"domain_scores_gemma":[0.9993325,0.0003175635,0.00008036817,0.00009845299,0.000132935,0.0000381639],"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":[0.0001497973,0.0001439852,0.002088495,0.00009851364,0.0001287621,0.0001262577,0.00008885089,0.806874,0.005110694,0.01096519,0.004805564,0.1694199],"study_design_scores_gemma":[0.000003011222,0.00001070395,0.0001149915,0.000002331739,0.000006966367,0.000009402493,0.000001848756,0.9975566,0.0002208324,0.001906825,0.0001627718,0.000003764663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07520994,0.00133098,0.9155638,0.000701973,0.0001062775,0.00006184895,0.0004901199,0.001871058,0.004663914],"genre_scores_gemma":[0.886143,0.0007668038,0.1015313,0.0004024603,0.00009392546,0.0001001088,0.000873012,0.00009736692,0.009992079],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02351565,"threshold_uncertainty_score":0.04675752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02140057928735824,"score_gpt":0.221194823307047,"score_spread":0.1997942440196888,"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."}}