{"id":"W2997261254","doi":"10.1609/aaai.v34i04.5945","title":"Memory Augmented Graph Neural Networks for Sequential Recommendation","year":2020,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":231,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Recommender system; Graph; Term (time); Artificial neural network; Variety (cybernetics); Machine learning; Artificial intelligence; Information retrieval; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000429502,0.0002076146,0.0002610361,0.00007648141,0.0001994973,0.0002795996,0.001521665,0.00009172141,0.00003650135],"category_scores_gemma":[0.0001447483,0.0001605659,0.0001772446,0.0005154554,0.00009039924,0.000467941,0.0003144905,0.0002325166,0.000006673853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002973395,"about_ca_system_score_gemma":0.00003406579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003015878,"about_ca_topic_score_gemma":0.000004627584,"domain_scores_codex":[0.9983723,0.00002517273,0.000575516,0.0004856102,0.0002377771,0.0003036313],"domain_scores_gemma":[0.9987525,0.00007203337,0.0004341558,0.0001866595,0.0004469769,0.0001077017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001272162,0.0001093766,0.00006774259,0.00008722474,0.00003939016,2.660231e-7,0.001249174,0.0002318881,0.01539234,0.6103715,0.00411831,0.3682056],"study_design_scores_gemma":[0.00004310848,0.0003435011,0.00001519677,0.00006232846,0.00001105987,0.000002426606,0.0002186723,0.6632116,0.2957557,0.03969303,0.0004465388,0.0001968202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005794753,0.0000144202,0.963756,0.02497427,0.0008581685,0.001009244,0.000007323793,0.0002674698,0.003318366],"genre_scores_gemma":[0.9934583,0.00001624003,0.005125931,0.001085283,0.0001744004,0.00008821877,0.000002335392,0.00001349505,0.00003578934],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9876636,"threshold_uncertainty_score":0.6547686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1317487524637631,"score_gpt":0.3104929346365802,"score_spread":0.1787441821728171,"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."}}