{"id":"W4311069763","doi":"10.1371/journal.pone.0278364","title":"Intelligent personalized shopping recommendation using clustering and supervised machine learning algorithms","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Sherbrooke; Mila - Quebec Artificial Intelligence Institute; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Recommender system; Computer science; Machine learning; Cluster analysis; Artificial intelligence; Random forest; Algorithm; Product (mathematics); Recurrent neural network; Set (abstract data type); Data mining; Artificial neural network","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001104291,0.001009836,0.001521456,0.002555216,0.0006748963,0.0009718695,0.001542029,0.00125075,0.001330825],"category_scores_gemma":[0.003424163,0.0006224375,0.001229918,0.001829077,0.0003751307,0.001247218,0.0005794463,0.0009559349,0.0009822891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001076319,"about_ca_system_score_gemma":0.001114925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02148877,"about_ca_topic_score_gemma":0.02573147,"domain_scores_codex":[0.9990001,0.0002579502,0.00006960907,0.0003437147,0.0002201115,0.000108502],"domain_scores_gemma":[0.9983901,0.0006805562,0.0001586573,0.0002465169,0.0004634024,0.00006078557],"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":[0.0002208622,0.0003645221,0.00431495,0.00009596183,0.0002194312,0.00007642671,0.00008293193,0.610612,0.002549771,0.00215917,0.00495608,0.3743479],"study_design_scores_gemma":[0.00000544694,0.00001230141,0.0002496018,0.000002747301,0.000006258535,0.000007969832,0.000005614327,0.9984888,0.0002983735,0.0007656927,0.0001525728,0.000004581397],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08215597,0.0008883392,0.9088496,0.0003338461,0.0001020156,0.0001685326,0.0004137931,0.004028745,0.003059212],"genre_scores_gemma":[0.5701353,0.0003515955,0.4235019,0.0002882608,0.0001492001,0.0001801486,0.001596539,0.0001653598,0.003631717],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02148877,"threshold_uncertainty_score":0.04272741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1195836760964014,"score_gpt":0.2723123222287879,"score_spread":0.1527286461323865,"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."}}