{"id":"W2213036792","doi":"10.1007/978-3-319-13365-2_9","title":"Application of Game-Theoretic Rough Sets in Recommender Systems","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Generality; Recommender system; Computer science; Property (philosophy); Set (abstract data type); Rough set; sort; Data mining; Artificial intelligence; Machine learning; Information retrieval","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":[0.006528454,0.0009962522,0.002143534,0.001596192,0.001018557,0.004201286,0.002662861,0.00179357,0.002648297],"category_scores_gemma":[0.02026961,0.0009001134,0.002065435,0.00227491,0.0026604,0.00482151,0.002902888,0.003259712,0.0003968577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002299601,"about_ca_system_score_gemma":0.001368706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003941992,"about_ca_topic_score_gemma":0.003121361,"domain_scores_codex":[0.9935737,0.004337632,0.0002998333,0.000411921,0.001208174,0.0001687998],"domain_scores_gemma":[0.9872987,0.01035235,0.0004324609,0.0008494385,0.000808791,0.0002583575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003940044,0.00007963814,0.0004627519,0.0002063215,0.0001657296,0.00008729572,0.0003275096,0.1375487,0.0003426391,0.8158848,0.001967744,0.04288736],"study_design_scores_gemma":[0.00001454005,0.00003898231,0.0001657326,0.00005506475,0.00003533631,0.00004855616,0.00006751507,0.3557169,0.000173564,0.6406958,0.002955793,0.00003214859],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007940821,0.002833475,0.9776102,0.001290274,0.0002255512,0.00007047117,0.00006859957,0.00006106244,0.009899543],"genre_scores_gemma":[0.5337145,0.00482043,0.4535513,0.0003314011,0.0006196846,0.0002415822,0.0001267236,0.00005047442,0.006543854],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006528454,"threshold_uncertainty_score":0.03452617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01542261779720944,"score_gpt":0.2419170805799392,"score_spread":0.2264944627827298,"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."}}