{"id":"W7124429115","doi":"10.1109/aiac68175.2025.11332292","title":"Integrating Structure-Aware Attention and Knowledge Graphs in Explainable Recommendation Systems","year":2025,"lang":"","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Knowledge graph; Attention network; Graph; Recommender system; Data modeling; Artificial neural network; Binary number; Preference; Binary relation","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":[0.000907522,0.0005991423,0.0006167769,0.001092617,0.0004250312,0.0008913977,0.001397863,0.001337652,0.001327373],"category_scores_gemma":[0.005495502,0.0004798902,0.0006907149,0.0009882969,0.0005948268,0.00331041,0.001015803,0.001371134,0.0002748364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001288685,"about_ca_system_score_gemma":0.0007891919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01809644,"about_ca_topic_score_gemma":0.02683129,"domain_scores_codex":[0.9994635,0.0001781474,0.00002832312,0.0001577185,0.0001301287,0.00004222645],"domain_scores_gemma":[0.9980906,0.001217093,0.0001683207,0.0002181554,0.0002447841,0.00006108994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001461377,0.0001664904,0.003086461,0.00020439,0.0001841707,0.0001836043,0.0003808849,0.745397,0.005616159,0.04205053,0.002116605,0.2004676],"study_design_scores_gemma":[0.000007457961,0.00002552157,0.0004750068,0.000008564216,0.00003080706,0.00002445327,0.00001225929,0.9800489,0.0008109987,0.01776424,0.0007810214,0.00001066949],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03916663,0.0005765258,0.957198,0.0005183339,0.00003631166,0.0000451377,0.0001184523,0.0007464776,0.001594186],"genre_scores_gemma":[0.8480789,0.0006832305,0.1478913,0.000214399,0.00005657822,0.0000758605,0.0002986123,0.00006952746,0.002631498],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01809644,"threshold_uncertainty_score":0.03598225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01545512136809092,"score_gpt":0.2819842083602709,"score_spread":0.26652908699218,"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."}}