{"id":"W4416017620","doi":"10.1145/3746252.3761152","title":"PriviRec: Confidential and Decentralized Graph Filtering for Recommender Systems","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche","keywords":"Recommender system; Graph; Filter (signal processing); Aggregate (composite); Overhead (engineering); Collaborative filtering; Adjacency matrix","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003278964,0.0009463865,0.001405301,0.0009489499,0.001356836,0.001800942,0.002914735,0.001982487,0.004165963],"category_scores_gemma":[0.0133005,0.0007124782,0.0009156892,0.001542253,0.001043234,0.00332888,0.002467354,0.002521448,0.002024387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001335116,"about_ca_system_score_gemma":0.003029302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008918393,"about_ca_topic_score_gemma":0.01952707,"domain_scores_codex":[0.9973641,0.0008409321,0.000105476,0.0006122922,0.0008783606,0.0001987877],"domain_scores_gemma":[0.9898854,0.003273916,0.0005044215,0.004817079,0.001227184,0.0002918274],"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":[0.0005765006,0.0003331684,0.002709553,0.0003721589,0.0002484958,0.0002434977,0.0003444783,0.474381,0.008551016,0.1050866,0.04320823,0.3639454],"study_design_scores_gemma":[0.00005678336,0.00004360766,0.0002803429,0.00001248722,0.00001769454,0.00007306776,0.00002596332,0.9594891,0.001703948,0.03245624,0.005817921,0.00002285964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0061659,0.000238115,0.9872114,0.0004244271,0.00007102008,0.0001030058,0.0003065899,0.003146335,0.002333253],"genre_scores_gemma":[0.4031288,0.0005354304,0.582889,0.0006133537,0.0002285059,0.0003594794,0.001621485,0.0005200615,0.01010386],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008918393,"threshold_uncertainty_score":0.01773298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01187131860750584,"score_gpt":0.2720351757435328,"score_spread":0.2601638571360269,"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."}}