{"id":"W4385301256","doi":"10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00203","title":"Long- and Short- Term Sequential Recommendation with Temporal Interval","year":2022,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"State Key Laboratory of Novel Software Technology; National Natural Science Foundation of China","keywords":"Computer science; Term (time); Preference; Sequence (biology); Transformer; Encoder; Recommender system; Artificial intelligence; Machine learning; Information retrieval; Human–computer interaction; Engineering","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":[0.001407696,0.001097161,0.001491677,0.001227082,0.0005131275,0.0007082783,0.002118881,0.0009256296,0.002280998],"category_scores_gemma":[0.003621238,0.0006556379,0.001319248,0.002329477,0.000387555,0.002070659,0.0006516796,0.001246063,0.0008511539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00102413,"about_ca_system_score_gemma":0.001167623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02965596,"about_ca_topic_score_gemma":0.04720265,"domain_scores_codex":[0.9987516,0.0002010891,0.00009599276,0.0004660634,0.0003474987,0.0001377043],"domain_scores_gemma":[0.9980437,0.0008339605,0.0002126016,0.0003411341,0.0004415601,0.0001271434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001044782,0.0006351012,0.01946856,0.0004774777,0.0005566406,0.0004998801,0.0003702588,0.4170622,0.01316247,0.01747829,0.00681254,0.5224318],"study_design_scores_gemma":[0.00001565142,0.00008130446,0.001336652,0.000007243023,0.00005086074,0.0000899894,0.00001027086,0.9944785,0.0007928109,0.002532443,0.0005892825,0.00001494396],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06891426,0.00152742,0.924444,0.0002894577,0.0001134321,0.0001193525,0.0006993437,0.001566796,0.002325951],"genre_scores_gemma":[0.8477116,0.000947856,0.1414554,0.0002293904,0.0002051686,0.0001627454,0.001456555,0.00009680771,0.007734512],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02965596,"threshold_uncertainty_score":0.0589667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03209571760856833,"score_gpt":0.2725952776552193,"score_spread":0.240499560046651,"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."}}