{"id":"W4412376966","doi":"10.1145/3726302.3729932","title":"Comprehending Knowledge Graphs with Large Language Models for Recommender Systems","year":2025,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Young Scientists Fund; National Natural Science Foundation of China; City University of Hong Kong","keywords":"Computer science; Recommender system; Knowledge graph; Natural language processing; Artificial intelligence; Information retrieval; Data science","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":[0.0004430233,0.000180657,0.0002828881,0.0002592821,0.0001909895,0.0002740351,0.000690616,0.00007594017,0.000003564018],"category_scores_gemma":[0.000003510029,0.0001312144,0.00008272734,0.0004262436,0.00001177772,0.000456859,0.0002032812,0.00009391376,0.000003603362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000533826,"about_ca_system_score_gemma":0.0000496976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001210749,"about_ca_topic_score_gemma":0.00008143239,"domain_scores_codex":[0.9987795,0.00007305397,0.000274406,0.0004084594,0.0001002074,0.0003643179],"domain_scores_gemma":[0.9989993,0.0001609177,0.00007282952,0.0006024244,0.0001036656,0.00006083726],"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":[0.000005369743,0.00007029848,0.00008584129,0.0001348996,0.00005443521,0.000001121101,0.0005983281,0.00002640195,0.00003533972,0.9577492,0.03792677,0.003311984],"study_design_scores_gemma":[0.00148841,0.0001827291,0.00005643121,0.0004276662,0.00002098149,0.00001707074,0.001375943,0.8387807,0.001783765,0.03122429,0.1241248,0.0005172471],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002481243,0.001242557,0.9141065,0.0003934434,0.0005435573,0.0006878283,0.000006912099,0.0007052798,0.08206572],"genre_scores_gemma":[0.9318759,0.00002066193,0.06174813,0.0003070027,0.00003334296,0.0003772614,0.00000666331,0.00001550922,0.005615484],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9316278,"threshold_uncertainty_score":0.5350769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02757635633335306,"score_gpt":0.2989864676665235,"score_spread":0.2714101113331705,"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."}}