{"id":"W2572321985","doi":"","title":"Building User Interest Profiles Using DBpedia in a Question Answering System.","year":2016,"lang":"en","type":"article","venue":"The Florida AI Research Society","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University; Université Laval","funders":"","keywords":"Computer science; Categorical variable; Information retrieval; Term (time); Set (abstract data type); User modeling; Question answering; Linked data; World Wide Web; Data mining; Semantic Web; User interface; Machine learning","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":[0.005798863,0.001031672,0.00123703,0.005110765,0.00131753,0.003455446,0.002113431,0.001683383,0.001462066],"category_scores_gemma":[0.01608335,0.0009477039,0.001518912,0.003280026,0.0003841046,0.005847138,0.002345328,0.002199593,0.002969642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001143585,"about_ca_system_score_gemma":0.001134502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009692865,"about_ca_topic_score_gemma":0.01881393,"domain_scores_codex":[0.9964975,0.001357086,0.0003808786,0.000950532,0.0006656916,0.0001483448],"domain_scores_gemma":[0.990576,0.004828892,0.0004583603,0.002094809,0.001583959,0.000457795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002368256,0.002646208,0.07012878,0.003256058,0.001748186,0.002680544,0.008694771,0.03958153,0.05616002,0.02962407,0.06747266,0.7156389],"study_design_scores_gemma":[0.0001134665,0.0004814305,0.01670055,0.0004371214,0.0006404511,0.001728036,0.00270152,0.7563742,0.04507234,0.05074383,0.1245954,0.0004114996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04208944,0.000957727,0.9200146,0.001077103,0.000151502,0.0009802777,0.01018526,0.01920065,0.005343521],"genre_scores_gemma":[0.238763,0.0005114797,0.7349573,0.0007380906,0.00008803369,0.0004505784,0.02103132,0.0004893455,0.00297081],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009692865,"threshold_uncertainty_score":0.03066766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1180784192410825,"score_gpt":0.3992222104433625,"score_spread":0.2811437912022801,"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."}}