{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007147092,0.0008753267,0.001037547,0.001862379,0.0006421685,0.0007304174,0.0005872418,0.0006157614,0.002998747],"category_scores_gemma":[0.00146996,0.000300048,0.0009835019,0.001021596,0.00008116206,0.001008183,0.0003924337,0.0005024483,0.002770642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004352902,"about_ca_system_score_gemma":0.0005564523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01465929,"about_ca_topic_score_gemma":0.02038833,"domain_scores_codex":[0.9993964,0.00007469415,0.0000848909,0.0001732594,0.000211327,0.00005935338],"domain_scores_gemma":[0.9991208,0.00009493971,0.00006687326,0.00005736099,0.000615151,0.00004494936],"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":[0.002173193,0.001170198,0.06773264,0.001356756,0.000950889,0.001221761,0.0006384792,0.007693986,0.1067684,0.002233153,0.0852486,0.7228118],"study_design_scores_gemma":[0.0004070452,0.001136439,0.07651558,0.0001739583,0.001442735,0.001450146,0.0006025014,0.8079082,0.0529705,0.002159124,0.05492866,0.0003052111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4618553,0.005892361,0.4327542,0.002061949,0.001393839,0.002557999,0.01892482,0.02953271,0.04502679],"genre_scores_gemma":[0.6711483,0.002086112,0.2861594,0.0005941134,0.0004563094,0.0005584718,0.01935744,0.0002089706,0.01943089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01465929,"threshold_uncertainty_score":0.02914792,"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."}}