{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000532696,0.0001984398,0.0002873483,0.0005185534,0.0002575328,0.00007754923,0.001501482,0.0002419437,0.00001963883],"category_scores_gemma":[0.00004479104,0.0001740735,0.00004646648,0.0004265839,0.00006089478,0.0001515631,0.00009239689,0.0001848713,0.00001862863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004716809,"about_ca_system_score_gemma":0.00004028754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004955102,"about_ca_topic_score_gemma":0.00004010729,"domain_scores_codex":[0.9983681,0.00005282091,0.0005023293,0.000676775,0.0001067563,0.0002932085],"domain_scores_gemma":[0.9975322,0.0001227573,0.0001722744,0.001961077,0.0001182322,0.000093407],"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":[0.00003391123,0.000554973,0.0001908381,0.0001760107,0.0002293277,0.000004466944,0.0007068354,0.00005700193,0.0002236383,0.4311,0.002193821,0.5645292],"study_design_scores_gemma":[0.001910682,0.003640692,0.0002551791,0.000612376,0.0001887851,0.0005073122,0.004069041,0.582297,0.03951544,0.03897239,0.3258161,0.002215096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001196635,0.0001742497,0.9932951,0.001855118,0.001094459,0.0008446942,0.00005045982,0.0007562902,0.0007330087],"genre_scores_gemma":[0.9612035,0.000335708,0.0377581,0.00006366914,0.00003158046,0.0004193561,0.00001503405,0.00002027196,0.000152814],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9600068,"threshold_uncertainty_score":0.709851,"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."}}