{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002183683,0.001754762,0.001292652,0.003344629,0.0008719831,0.001855374,0.001860025,0.001497012,0.002161144],"category_scores_gemma":[0.0125772,0.00105205,0.002293216,0.00305773,0.0007794196,0.004348414,0.002051855,0.002439734,0.0014163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001441885,"about_ca_system_score_gemma":0.001369807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01734603,"about_ca_topic_score_gemma":0.03233318,"domain_scores_codex":[0.9980423,0.0009471607,0.0001435405,0.0004039158,0.0003807705,0.00008240435],"domain_scores_gemma":[0.9930796,0.004907134,0.0004228131,0.0008970399,0.0005895824,0.0001037923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002719133,0.0002646791,0.003712922,0.000808417,0.0005064607,0.000818388,0.001113014,0.4971993,0.006265234,0.06023129,0.01738484,0.4114236],"study_design_scores_gemma":[0.00002062944,0.00002605919,0.0002641249,0.00003515568,0.00006201504,0.00007032904,0.00009975857,0.936452,0.000723989,0.05794908,0.004272948,0.00002389922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00675251,0.0008042085,0.9884594,0.0005100546,0.00004193642,0.00007739897,0.0005728346,0.001941843,0.0008399239],"genre_scores_gemma":[0.2832146,0.001945516,0.7050853,0.0008361917,0.000198659,0.000470144,0.004885389,0.0003979723,0.00296624],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01734603,"threshold_uncertainty_score":0.03449011,"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."}}