{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008190117,0.00218667,0.00469273,0.005900867,0.002122808,0.00503979,0.003526854,0.002838099,0.003236203],"category_scores_gemma":[0.03308515,0.001043655,0.002785147,0.007359417,0.001313186,0.006895958,0.003176692,0.003106219,0.003241097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001372552,"about_ca_system_score_gemma":0.00223155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01908358,"about_ca_topic_score_gemma":0.02329001,"domain_scores_codex":[0.9912241,0.003989065,0.0005528287,0.001699883,0.002273069,0.0002609889],"domain_scores_gemma":[0.9783422,0.01219099,0.0008194338,0.004170578,0.003986342,0.000490514],"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":[0.0005326066,0.0004432847,0.008630075,0.0008625418,0.001544569,0.00009176059,0.0004867462,0.1161636,0.002625019,0.0190814,0.01853196,0.8310065],"study_design_scores_gemma":[0.00003791685,0.00009414155,0.001708979,0.0001100635,0.0001881217,0.00009167338,0.0001488623,0.9208778,0.001499088,0.06865013,0.006518393,0.0000749091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004801642,0.001596984,0.9894952,0.000445132,0.0001808583,0.0001627532,0.0003881938,0.00175627,0.001172961],"genre_scores_gemma":[0.1385353,0.001490497,0.8539829,0.0004010736,0.0004965313,0.0002697296,0.001393831,0.0004149917,0.003015122],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01908358,"threshold_uncertainty_score":0.04331398,"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."}}