{"id":"W4403459152","doi":"10.3390/electronics13204073","title":"UDIS: Enhancing Collaborative Filtering with Fusion of Dimensionality Reduction and Semantic Similarity","year":2024,"lang":"en","type":"article","venue":"Electronics","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Dimensionality reduction; Similarity (geometry); Collaborative filtering; Semantic similarity; Computer science; Fusion; Artificial intelligence; Reduction (mathematics); Information retrieval; Pattern recognition (psychology); Natural language processing; Mathematics; Recommender system; Linguistics; Philosophy","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":[0.0003130432,0.00008154281,0.0001256335,0.00005422281,0.00007475082,0.00007555632,0.00009540642,0.00003576192,0.000001911529],"category_scores_gemma":[0.000005279009,0.00006345956,0.00001670835,0.0003245058,0.00002037595,0.0002772917,0.00008304006,0.0001193331,4.632695e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005905093,"about_ca_system_score_gemma":0.0001238367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002010748,"about_ca_topic_score_gemma":0.00006191123,"domain_scores_codex":[0.9992858,0.0000504706,0.0001465885,0.0002410883,0.000134366,0.0001416957],"domain_scores_gemma":[0.9996477,0.00003560253,0.00004836944,0.0001774637,0.00006557455,0.00002526002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002826086,0.00008691377,0.0001945943,0.0006722992,0.0001471206,0.00002414856,0.004180161,0.00004688974,0.7280964,0.218942,0.001600216,0.04598102],"study_design_scores_gemma":[0.0001559561,0.0006738977,0.0003740265,0.0005604656,0.00002095531,0.0001558634,0.0001413962,0.02658764,0.9492193,0.009572932,0.01227741,0.0002601351],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4593101,0.01049053,0.5278796,0.001064206,0.0002350688,0.0002831946,0.000002438992,0.0003045982,0.0004303087],"genre_scores_gemma":[0.9872226,0.000406555,0.01227255,0.00001060698,0.00002376938,0.000009244741,0.000001307707,0.00000573964,0.00004767834],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5279125,"threshold_uncertainty_score":0.2587806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008647927301655057,"score_gpt":0.2466911802071753,"score_spread":0.2380432529055202,"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."}}