{"id":"W1989587422","doi":"10.1145/1864708.1864741","title":"Learning in efficient tag recommendation","year":2010,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Recommender system; Search engine indexing; Tag system; Information retrieval; Process (computing); Set (abstract data type); Resource (disambiguation); Adaptation (eye); Collaborative filtering; World Wide Web; Data mining","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":[0.005036725,0.00113568,0.002533244,0.002173225,0.001558273,0.002823753,0.002521141,0.002693251,0.004703236],"category_scores_gemma":[0.01957482,0.001141968,0.001176762,0.004233688,0.001930499,0.006736124,0.002507111,0.002151534,0.003755416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001919102,"about_ca_system_score_gemma":0.001750929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009327555,"about_ca_topic_score_gemma":0.009242164,"domain_scores_codex":[0.9950016,0.00207987,0.0003515925,0.001271966,0.0009200604,0.0003748956],"domain_scores_gemma":[0.9863735,0.008357068,0.0005990827,0.003117104,0.001377022,0.0001761778],"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":[0.0004983441,0.0003328743,0.003333968,0.0004958583,0.000187585,0.0002629439,0.0004532248,0.2809223,0.004453551,0.06666787,0.01482334,0.6275682],"study_design_scores_gemma":[0.00008438446,0.00007807592,0.0005697986,0.00002911789,0.00004436836,0.0002013565,0.00007342084,0.907284,0.003720674,0.07939718,0.00848018,0.00003736091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01037749,0.001027099,0.9842201,0.0004858737,0.00008868548,0.00009777479,0.0001893529,0.001223964,0.002289589],"genre_scores_gemma":[0.2808409,0.001450796,0.7050601,0.0005164369,0.0004288946,0.0003774249,0.001262218,0.0002619606,0.009801194],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009327555,"threshold_uncertainty_score":0.02663708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01076132458965088,"score_gpt":0.2519853760337522,"score_spread":0.2412240514441013,"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."}}