{"id":"W1998821701","doi":"10.1109/bdcloud.2014.51","title":"Incorporating User Reviews as Implicit Feedback for Improving Recommender Systems","year":2014,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Recommender system; Computer science; Collaborative filtering; World Wide Web; Information retrieval; Data science","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":[0.002222397,0.0002344542,0.0004543776,0.00009923459,0.0002097475,0.0005396178,0.000898336,0.0001099706,0.000007865603],"category_scores_gemma":[0.0001198848,0.0001779098,0.0001425323,0.0002119423,0.000011294,0.0006396528,0.0002904557,0.0001199296,0.00007210053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006409386,"about_ca_system_score_gemma":0.00003361336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006156771,"about_ca_topic_score_gemma":0.00002964308,"domain_scores_codex":[0.9980282,0.0001957045,0.0007049858,0.0005432988,0.0001537739,0.0003740133],"domain_scores_gemma":[0.9982253,0.0002014465,0.0004158675,0.0009106981,0.000122112,0.000124541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002447011,0.00003437711,0.0003998022,0.000402432,0.00001674732,4.346178e-7,0.0001355002,0.000004298737,0.001817785,0.6766987,0.09745625,0.2230312],"study_design_scores_gemma":[0.000471514,0.0003513361,0.0000686699,0.000181824,0.00001031265,0.00004696578,0.00006864761,0.08370741,0.002781638,0.01329446,0.898428,0.0005892747],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001906455,0.000256008,0.9725688,0.001071725,0.0009680699,0.001243131,9.65581e-7,0.0005249205,0.02317581],"genre_scores_gemma":[0.4892486,0.00003671909,0.500179,0.00305523,0.0006578185,0.001061401,0.000007428747,0.00005603652,0.005697789],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8009717,"threshold_uncertainty_score":0.7254952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03461982996384694,"score_gpt":0.2835843166310714,"score_spread":0.2489644866672244,"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."}}