{"id":"W3091442083","doi":"10.18280/isi.250413","title":"A Novel Tourist Attraction Recommendation System Based on Improved Visual Bayesian Personalized Ranking","year":2020,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"E-commerce and Technology Innovations","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ranking (information retrieval); Attraction; Bayesian probability; Computer science; Tourism; Tourist attraction; Recommender system; Artificial intelligence; Information retrieval; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003881353,0.0002314302,0.0002358791,0.0005240054,0.0005667203,0.0005197578,0.0001758309,0.0001809916,0.0001404419],"category_scores_gemma":[0.000316722,0.0002378284,0.00009125507,0.001078377,0.00009266689,0.004452875,0.00005237002,0.0002653647,0.0002666349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002723763,"about_ca_system_score_gemma":0.00004267995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002906714,"about_ca_topic_score_gemma":0.00001941119,"domain_scores_codex":[0.9986598,0.000013789,0.0006458304,0.0001915469,0.0002188927,0.0002701085],"domain_scores_gemma":[0.9987833,0.00004893176,0.0006515082,0.0001507367,0.0003455855,0.00001987091],"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":[0.002246049,0.0007057524,0.01922056,0.008746582,0.0004332889,0.00001241827,0.004182384,0.003794565,0.0209777,0.2898816,0.01638472,0.6334143],"study_design_scores_gemma":[0.002277728,0.00008566345,0.003030902,0.0002753674,0.00007517029,0.000007564475,0.00426526,0.9615154,0.0004200027,0.0001983777,0.02740461,0.0004439437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09148099,0.000006570046,0.8487353,0.01036684,0.0007802034,0.001099235,0.00003015872,0.00189375,0.04560694],"genre_scores_gemma":[0.9903412,7.027137e-7,0.001403117,0.006805881,0.0004754363,0.00009717554,0.0008427136,0.00002380211,0.000009981155],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9577209,"threshold_uncertainty_score":0.9698362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02218367006231552,"score_gpt":0.2368782147885249,"score_spread":0.2146945447262094,"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."}}