{"id":"W3185982650","doi":"10.1016/j.mlwa.2021.100114","title":"Restaurant recommender system based on sentiment analysis","year":2021,"lang":"en","type":"article","venue":"Machine Learning with Applications","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Recommender system; Computer science; Precision and recall; Information retrieval; Similarity (geometry); Context (archaeology); Recall; Quality (philosophy); Sentiment analysis; Service (business); Semantic similarity; Semantic analysis (machine learning); World Wide Web; Artificial intelligence","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":[0.0002970657,0.0001488106,0.0002364346,0.0002959425,0.0003943476,0.0002220462,0.000331302,0.00003260855,0.00009955824],"category_scores_gemma":[0.00001010151,0.0001226626,0.0001526059,0.002448062,0.00001485533,0.00007402399,0.00008012092,0.0002099443,0.00008888694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006907636,"about_ca_system_score_gemma":0.00005292004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003344783,"about_ca_topic_score_gemma":0.0000225415,"domain_scores_codex":[0.9984538,0.0001716949,0.0002456583,0.0005559804,0.0003636217,0.0002092491],"domain_scores_gemma":[0.9986665,0.0001451384,0.0001632918,0.0008062224,0.0001207781,0.00009812289],"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":[0.00002361347,0.0005499285,0.1705936,0.00005967903,0.00154928,0.0000517068,0.0003997342,0.7263039,0.0003282127,0.07215884,0.0008406227,0.02714087],"study_design_scores_gemma":[0.0002982265,0.00003776255,0.004175128,0.00002159277,0.0002272088,0.000004065819,0.0001161709,0.9643217,0.0003880016,0.00001202667,0.0302278,0.0001703658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0008644515,0.00008675383,0.9907916,0.002973121,0.00002759825,0.0001383433,0.000002823618,0.0002469165,0.004868456],"genre_scores_gemma":[0.9272614,0.000004624038,0.07058109,0.0004172371,0.00004460139,0.0001682581,0.0001698388,0.0000140647,0.001338938],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9263969,"threshold_uncertainty_score":0.5002037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01087090913641009,"score_gpt":0.2466184941477989,"score_spread":0.2357475850113888,"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."}}