{"id":"W4366967952","doi":"10.1109/wi-iat55865.2022.00115","title":"A Survey of Explainable E-Commerce Recommender Systems","year":2022,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Recommender system; Information overload; Computer science; E-commerce; Field (mathematics); Loyalty; Quality (philosophy); World Wide Web; Information retrieval; Marketing; Business","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":[0.003242766,0.0009197561,0.001097903,0.002449755,0.0006626368,0.001810971,0.001836256,0.001707598,0.004973456],"category_scores_gemma":[0.01139751,0.0006228894,0.001218063,0.004455045,0.0003368919,0.002848528,0.0008608379,0.001167707,0.002055682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007281881,"about_ca_system_score_gemma":0.001050993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005678795,"about_ca_topic_score_gemma":0.005757814,"domain_scores_codex":[0.9976571,0.000744581,0.0002810498,0.000281762,0.0009377318,0.00009776497],"domain_scores_gemma":[0.9929938,0.004647379,0.0002868465,0.0005878091,0.001400736,0.00008349373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001592883,0.0001841753,0.007008295,0.004676627,0.0004300313,0.0002800074,0.000483492,0.01120952,0.002234304,0.02823017,0.01950328,0.9256008],"study_design_scores_gemma":[0.0001477299,0.0008042431,0.02310743,0.004309619,0.001348407,0.003159958,0.0007081079,0.1692313,0.00623304,0.05586409,0.7347008,0.0003852619],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.04019545,0.4509968,0.4631081,0.006728466,0.001053212,0.0007000128,0.002484727,0.00168743,0.03304576],"genre_scores_gemma":[0.2086547,0.4699009,0.2934462,0.002082364,0.001478673,0.0004535435,0.005753525,0.0001772888,0.01805286],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.005678795,"threshold_uncertainty_score":0.01714957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05737990568654881,"score_gpt":0.2688370842935954,"score_spread":0.2114571786070466,"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."}}