{"id":"W4391427667","doi":"10.1016/j.ins.2024.120253","title":"Towards privacy-preserving category-aware POI recommendation over encrypted LBSN data","year":2024,"lang":"en","type":"article","venue":"Information Sciences","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"China Postdoctoral Science Foundation; Natural Sciences and Engineering Research Council of Canada; Natural Science Foundation of Shaanxi Province; National Natural Science Foundation of China; Natural Science Foundation of Jilin Province","keywords":"Computer science; Encryption; Outsourcing; Cloud computing; Data mining; Merge (version control); Location-based service; Popularity; Information retrieval; Computer security; Computer network","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":[0.002146522,0.0007596261,0.002247889,0.001943144,0.001361146,0.0026632,0.002809071,0.001713852,0.001506634],"category_scores_gemma":[0.01222567,0.0006241772,0.001142957,0.005413892,0.0009172811,0.005006971,0.003412581,0.001732815,0.001636981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009674061,"about_ca_system_score_gemma":0.00265984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007865201,"about_ca_topic_score_gemma":0.01066368,"domain_scores_codex":[0.9957204,0.0008521527,0.0003037738,0.0006701223,0.001882969,0.0005706136],"domain_scores_gemma":[0.9924556,0.001963644,0.00048019,0.00369676,0.001183324,0.0002204584],"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":[0.001808865,0.0007321553,0.01758162,0.0007423554,0.0004854023,0.00106958,0.001151381,0.234664,0.03863539,0.07886044,0.02742969,0.5968391],"study_design_scores_gemma":[0.00002898895,0.0001003434,0.001296709,0.00003985091,0.00005882567,0.0006205339,0.0002703043,0.9407653,0.007143929,0.0447712,0.004861125,0.00004293742],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04867224,0.0009866429,0.9415607,0.0007542616,0.0002081678,0.0002451472,0.00225764,0.0020018,0.003313421],"genre_scores_gemma":[0.7786461,0.001048539,0.2074034,0.0005221299,0.0002828061,0.0001831577,0.004555414,0.0001284784,0.007229986],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007865201,"threshold_uncertainty_score":0.01563883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08274629982190981,"score_gpt":0.3455818912581672,"score_spread":0.2628355914362575,"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."}}