{"id":"W4285308692","doi":"10.18653/v1/2022.nlp4convai-1.17","title":"Toward Knowledge-Enriched Conversational Recommendation Systems","year":2022,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Research (Canada)","funders":"National Research Foundation Singapore; National Research Foundation","keywords":"Computer science; Recommender system; Knowledge graph; Natural language processing; Scale (ratio); Artificial intelligence; Information retrieval; World Wide Web; Human–computer interaction","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":[0.0003649876,0.00004948207,0.00006163316,0.00006647741,0.0001447351,0.0000678223,0.0003872884,0.00001257798,0.0004291411],"category_scores_gemma":[0.00001222274,0.00005099686,0.00002264649,0.0001846502,0.00000449421,0.0002146113,0.0003471664,0.00008321054,0.00007417388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001339439,"about_ca_system_score_gemma":0.00007687231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004832777,"about_ca_topic_score_gemma":8.778916e-7,"domain_scores_codex":[0.9992861,0.00009963976,0.0001444578,0.0002115921,0.000151675,0.0001065917],"domain_scores_gemma":[0.9996278,0.00006117183,0.00004239736,0.0001897647,0.0000451878,0.00003372577],"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":[0.000002163498,0.00006267823,0.0003440345,0.00001370764,0.00001472769,0.000001978147,0.002253764,0.007709842,0.0001960458,0.9498867,0.01167016,0.02784424],"study_design_scores_gemma":[0.0001742208,0.00001880354,0.0001223304,5.587316e-7,0.000001127055,0.00001251765,0.0002952539,0.9325495,0.00002315966,0.001385283,0.06534087,0.00007636568],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001257602,0.00004704804,0.9685625,0.002825166,0.001585749,0.0001037403,0.000001393962,0.0001760143,0.02544074],"genre_scores_gemma":[0.985519,0.000001148291,0.01160353,0.0002731835,0.00006850182,0.0000481379,0.00001425732,0.000003241166,0.002468989],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9842614,"threshold_uncertainty_score":0.4698794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06068580457003696,"score_gpt":0.2693948918523879,"score_spread":0.2087090872823509,"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."}}