{"id":"W4401834057","doi":"10.18280/ria.380417","title":"PRMNBR: Personalized Recommendation Model for Next Basket Recommendation Using User’s Long-Term Preference, Short-Term Preference, and Repetition Behaviour","year":2024,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preference; Term (time); Computer science; Information retrieval; Recommender system; Repetition (rhetorical device); Statistics; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001140465,0.001175065,0.001790619,0.001183368,0.0005079698,0.0009366964,0.003380212,0.001688168,0.00455428],"category_scores_gemma":[0.002204458,0.0008624968,0.001523984,0.001499067,0.0003001501,0.00163544,0.0008143802,0.002416835,0.004318272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001167661,"about_ca_system_score_gemma":0.001594242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06270235,"about_ca_topic_score_gemma":0.08027118,"domain_scores_codex":[0.9993715,0.0001152468,0.00004972487,0.0002453386,0.0001420253,0.00007624322],"domain_scores_gemma":[0.9995356,0.0001367496,0.00004606375,0.00008106512,0.0001696762,0.00003087794],"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":[0.0008536761,0.0006745436,0.00749405,0.0003478892,0.0005006882,0.0003067825,0.0001954435,0.3903806,0.006562604,0.007006766,0.03094816,0.5547288],"study_design_scores_gemma":[0.00003057439,0.00006594458,0.000566055,0.00001435601,0.00003509181,0.00007367792,0.00000720181,0.9957355,0.0004673503,0.001219754,0.001766726,0.00001772856],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.032743,0.002419228,0.9473293,0.0009915642,0.0002886631,0.000270565,0.003649687,0.008251463,0.00405649],"genre_scores_gemma":[0.4215926,0.002375334,0.5440259,0.001116547,0.000294463,0.0008593483,0.008472256,0.0003845084,0.02087912],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06270235,"threshold_uncertainty_score":0.1246748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2133542736628898,"score_gpt":0.3443419363235555,"score_spread":0.1309876626606657,"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."}}