{"id":"W4399699011","doi":"10.1007/978-3-031-62362-2_40","title":"Dynamic Hybrid Recommendation System for E-Commerce: Overcoming Challenges of Sparse Data and Anonymity","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Fredericton; University of New Brunswick","funders":"","keywords":"Computer science; Anonymity; Recommender system; E-commerce; Data mining; Theoretical computer science; Computer security; Information retrieval; World Wide Web","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":[0.0024144,0.0005412403,0.002039449,0.001115759,0.001315202,0.002692002,0.00256957,0.001556147,0.003850905],"category_scores_gemma":[0.003702469,0.0005351545,0.0007405067,0.002478419,0.0006014614,0.004388229,0.002100056,0.001769827,0.002034233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006934069,"about_ca_system_score_gemma":0.001108949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004392839,"about_ca_topic_score_gemma":0.006697201,"domain_scores_codex":[0.9982128,0.0005214243,0.00009829664,0.0003776564,0.0006173305,0.0001725162],"domain_scores_gemma":[0.9965116,0.001398053,0.0001245049,0.001078635,0.0007115456,0.0001756586],"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":[0.0009879419,0.000543121,0.003656382,0.0003213497,0.0004707313,0.0003459617,0.0003433977,0.09569827,0.01995913,0.05737153,0.03510758,0.7851946],"study_design_scores_gemma":[0.00003918129,0.0001514118,0.0005905607,0.0000123339,0.00007645025,0.0003145561,0.00007333054,0.9660764,0.002946014,0.02174725,0.007914816,0.00005767984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03194429,0.001803789,0.9578801,0.0006534189,0.0002844545,0.00009511528,0.0003022561,0.001801596,0.005235069],"genre_scores_gemma":[0.5863471,0.001529448,0.3921544,0.0005290371,0.0006190723,0.0001470584,0.0008844305,0.0002152196,0.01757419],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004392839,"threshold_uncertainty_score":0.01288259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0465083819281543,"score_gpt":0.2893807841379523,"score_spread":0.242872402209798,"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."}}