{"id":"W4385882083","doi":"10.1109/bmsb58369.2023.10211188","title":"Novel Personalized Multimedia Recommendation Systems Using Tensor Singular-Value-Decomposition","year":2023,"lang":"en","type":"article","venue":"","topic":"Tensor decomposition and applications","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Singular value decomposition; Computer science; Recommender system; Multimedia; Tensor decomposition; Decomposition; Tensor (intrinsic definition); Information retrieval; Artificial intelligence; 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":[0.001138956,0.001271282,0.001509466,0.001590957,0.0007026554,0.0009908349,0.00126555,0.001002257,0.002342526],"category_scores_gemma":[0.002987625,0.0004761252,0.001451836,0.002086507,0.0003345907,0.001699487,0.0006808651,0.001023229,0.001371473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006110851,"about_ca_system_score_gemma":0.0008266526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01703792,"about_ca_topic_score_gemma":0.02183439,"domain_scores_codex":[0.9990126,0.0002022052,0.00008617989,0.0002595846,0.0003392225,0.0001001586],"domain_scores_gemma":[0.9987605,0.0003111308,0.0001394484,0.0001870559,0.000520531,0.00008138524],"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":[0.0006134168,0.0004389364,0.005129497,0.0003505213,0.0005161223,0.000332768,0.0002547276,0.188156,0.03654078,0.00880729,0.01449565,0.7443643],"study_design_scores_gemma":[0.00002719576,0.0001132067,0.0006854361,0.00001160723,0.00007080808,0.000102932,0.00003739329,0.9915236,0.003699968,0.001755529,0.001938249,0.00003403662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03528959,0.001698451,0.9580178,0.0002823281,0.0001651002,0.0001346593,0.000342823,0.001706338,0.002362883],"genre_scores_gemma":[0.3971723,0.001765825,0.5922996,0.0003281695,0.0002377484,0.0002023719,0.001374795,0.0001293818,0.006489863],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01703792,"threshold_uncertainty_score":0.03387749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1190994709113317,"score_gpt":0.3896650378705325,"score_spread":0.2705655669592008,"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."}}