{"id":"W7138919059","doi":"10.5220/0006931200002053","title":"Beyond k-NN: Combining Cluster Analysis and Classification for Recommender Systems","year":2018,"lang":"","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada; University of Ottawa","funders":"","keywords":"Recommender system; Cluster (spacecraft); Feature (linguistics); Cluster analysis; Field (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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002332529,0.0004410801,0.0008496438,0.0007461504,0.0007136547,0.001720954,0.0007960967,0.0003480491,0.00006141083],"category_scores_gemma":[0.00003985863,0.0003944786,0.0002902707,0.001444662,0.0001892649,0.0009347649,0.0004359062,0.0001869697,0.00003188108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001226498,"about_ca_system_score_gemma":0.00007320751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003682314,"about_ca_topic_score_gemma":0.0001988857,"domain_scores_codex":[0.9961419,0.0003773012,0.001188009,0.001280829,0.0003495878,0.0006624464],"domain_scores_gemma":[0.996718,0.000432554,0.0006273034,0.001296631,0.000652606,0.0002729238],"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":[0.00009036852,0.0004267501,0.0167973,0.0006233469,0.004142704,0.000001660918,0.006592325,0.00001031062,0.0005411524,0.5020383,0.2411196,0.2276162],"study_design_scores_gemma":[0.000838933,0.0007502933,0.003392713,0.00009256614,0.0005607816,0.00001825425,0.0005619526,0.9310572,0.0005457211,0.003323919,0.05821416,0.0006435664],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001245299,0.0004505203,0.961148,0.005543991,0.002395202,0.00144009,0.00001706949,0.0002742642,0.02748562],"genre_scores_gemma":[0.9447426,0.0001146229,0.04928326,0.001232652,0.0005424511,0.0002614557,0.00001973317,0.00003316093,0.003770071],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9434973,"threshold_uncertainty_score":0.9998507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05357666738645059,"score_gpt":0.3049387783222676,"score_spread":0.251362110935817,"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."}}