{"id":"W2139420544","doi":"10.1145/2036264.2036266","title":"Efficient Tag Recommendation for Real-Life Data","year":2011,"lang":"en","type":"article","venue":"ACM Transactions on Intelligent Systems and Technology","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Scalability; Recommender system; Adaptation (eye); Content adaptation; Process (computing); Task (project management); Tag system; Set (abstract data type); Resource (disambiguation); Information retrieval; Data mining; Database; Human–computer interaction; Ubiquitous computing","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":[0.004895907,0.001124765,0.001892718,0.003542719,0.001556393,0.002268865,0.002694141,0.002198927,0.001765126],"category_scores_gemma":[0.01382718,0.0008337153,0.001072455,0.00552351,0.0005677655,0.00369419,0.001198446,0.001506017,0.002548576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001238912,"about_ca_system_score_gemma":0.001238052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01573521,"about_ca_topic_score_gemma":0.03632589,"domain_scores_codex":[0.9969705,0.000902473,0.0002698135,0.0009559047,0.0007319031,0.0001694584],"domain_scores_gemma":[0.9894031,0.004684094,0.0004714394,0.003749948,0.00148437,0.0002070298],"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":[0.001031376,0.0005931547,0.01584511,0.0008034347,0.0005538233,0.0006577846,0.000830584,0.1377856,0.0409885,0.005275837,0.02713452,0.7685004],"study_design_scores_gemma":[0.00007777551,0.0001064057,0.003765527,0.00004072921,0.0000852179,0.000396273,0.0002955931,0.9623744,0.01400807,0.008814751,0.009965078,0.00007004567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06143807,0.001560105,0.9172812,0.0006666222,0.0001297446,0.0002867839,0.00260461,0.01443045,0.001602418],"genre_scores_gemma":[0.220341,0.0005098536,0.7716801,0.0001842634,0.00006376346,0.0001740414,0.004807552,0.0002366824,0.002002743],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01573521,"threshold_uncertainty_score":0.03128725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1228393011481122,"score_gpt":0.3094453650804747,"score_spread":0.1866060639323625,"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."}}