{"id":"W2100359483","doi":"10.1109/icws.2011.61","title":"Collaborative Filtering Based Service Ranking Using Invocation Histories","year":2011,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Collaborative filtering; Computer science; Recommender system; Ranking (information retrieval); Information retrieval; Information overload; Web service; Similarity (geometry); Service (business); Matching (statistics); Quality of service; Data mining; Quality (philosophy); Database; World Wide Web; Artificial intelligence; Computer network","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002050878,0.00008493162,0.00009912771,0.00007893953,0.0001105166,0.00008113543,0.0003357732,0.00003616165,0.00002447574],"category_scores_gemma":[0.00000650294,0.0000765078,0.00001768204,0.000433871,0.000008050662,0.0006112023,0.00008617878,0.00004012091,0.000003865871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008543133,"about_ca_system_score_gemma":0.00007618863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008836653,"about_ca_topic_score_gemma":0.0001425958,"domain_scores_codex":[0.9993727,0.00005453609,0.000158328,0.0001894945,0.0001055977,0.000119343],"domain_scores_gemma":[0.9993774,0.00002161135,0.00008565612,0.0003015986,0.0001819775,0.00003174188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004409387,0.0003335612,0.01009169,0.0004495688,0.0001159372,0.00004183476,0.1074896,0.0001399687,0.09440749,0.7298859,0.004616293,0.05238407],"study_design_scores_gemma":[0.0006463335,0.0001601921,0.001973502,0.000209945,0.00001465402,0.00002134673,0.001040435,0.4181503,0.5416779,0.008484883,0.02674313,0.0008773424],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004124782,0.00003365228,0.978705,0.0002090105,0.0003179327,0.0001290838,3.958721e-7,0.0003411843,0.01613893],"genre_scores_gemma":[0.5884008,5.859205e-7,0.4111461,0.0003840563,0.00001788463,0.00001172563,5.282799e-7,0.00000448609,0.00003390499],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.721401,"threshold_uncertainty_score":0.3119898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0780366164483595,"score_gpt":0.2589619154536387,"score_spread":0.1809252990052792,"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."}}