{"id":"W4386791067","doi":"10.1007/s42979-023-02166-5","title":"A Survey and Taxonomy of Sequential Recommender Systems for E-commerce Product Recommendation","year":2023,"lang":"en","type":"article","venue":"SN Computer Science","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Recommender system; Computer science; E-commerce; Product (mathematics); Collaborative filtering; Information retrieval; Revenue; Data science; Data mining; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005099593,0.0001971675,0.0003375563,0.0005148179,0.0003249965,0.0004904109,0.001308396,0.00004986528,0.000001800134],"category_scores_gemma":[0.00007035241,0.0001799806,0.00005816213,0.001799589,0.0001781306,0.001143585,0.0008652717,0.0001018074,0.000006347858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006563305,"about_ca_system_score_gemma":0.0001776238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003611411,"about_ca_topic_score_gemma":0.00001953661,"domain_scores_codex":[0.9975982,0.000217782,0.000524174,0.0008667349,0.0003106076,0.000482442],"domain_scores_gemma":[0.9981015,0.0003460045,0.0002916492,0.0007269005,0.0004001869,0.0001337909],"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":[0.00001950896,0.0001579998,0.01325205,0.0004193183,0.00006931902,0.000002633044,0.001194139,0.0002360025,0.001507046,0.03379748,0.1023836,0.8469609],"study_design_scores_gemma":[0.0006510799,0.0004170294,0.02894505,0.0001127984,0.000006402973,0.00003957412,0.00003944633,0.8983175,0.003662667,0.001227734,0.06599938,0.0005813048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005726567,0.00007162995,0.9885986,0.001283505,0.002485626,0.001133253,0.00002432216,0.0003786451,0.0002977787],"genre_scores_gemma":[0.8923144,0.00006626436,0.1067836,0.0001768116,0.000209574,0.0003056371,0.00003000065,0.00001734931,0.00009632776],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8980815,"threshold_uncertainty_score":0.7339396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1192941130776285,"score_gpt":0.3121814208607136,"score_spread":0.1928873077830851,"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."}}