{"id":"W2129168172","doi":"10.1109/wiiat.2008.99","title":"Imputed Neighborhood Based Collaborative Filtering","year":2008,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Imputation (statistics); Collaborative filtering; Computer science; Recommender system; Correlation; Extension (predicate logic); Bayesian probability; Pearson product-moment correlation coefficient; Data mining; Missing data; Machine learning; Artificial intelligence; Statistics; Mathematics","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":[0.007996731,0.0009802436,0.00324959,0.00184787,0.001562173,0.001867677,0.005030717,0.002059964,0.002656902],"category_scores_gemma":[0.03097782,0.0007370618,0.001741001,0.003493438,0.0009598836,0.003281476,0.001798638,0.001952964,0.001156888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001162367,"about_ca_system_score_gemma":0.00136343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01481505,"about_ca_topic_score_gemma":0.01572609,"domain_scores_codex":[0.9905414,0.004585891,0.000476273,0.001992682,0.002004743,0.0003989982],"domain_scores_gemma":[0.9758739,0.01341688,0.001252611,0.005478221,0.003664982,0.0003135311],"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":[0.0008486744,0.0003423759,0.0129713,0.000336798,0.0006423609,0.00034163,0.0006681,0.5392521,0.002023366,0.03668592,0.008511298,0.3973761],"study_design_scores_gemma":[0.00004447236,0.0001091809,0.001236131,0.00002710622,0.00007152484,0.0001964947,0.00006728749,0.9781986,0.001121702,0.01609791,0.002783797,0.00004572711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01384482,0.000409061,0.9834651,0.0001855941,0.00005434084,0.00006874392,0.0002457543,0.0004515503,0.001275073],"genre_scores_gemma":[0.4754316,0.0005687841,0.5178719,0.0003217838,0.0001688654,0.0002182833,0.001306114,0.00008281954,0.004029993],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01481505,"threshold_uncertainty_score":0.04229128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01933516844964202,"score_gpt":0.2262032700261886,"score_spread":0.2068681015765466,"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."}}