{"id":"W2980200266","doi":"10.1007/s42979-019-0026-8","title":"Clustering and Association Rules for Web Service Discovery and Recommendation: A Systematic Literature Review","year":2019,"lang":"en","type":"article","venue":"SN Computer Science","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Cluster analysis; Association rule learning; Knowledge extraction; Data extraction; Data science; Systematic review; Information retrieval; Web service; Service (business); Data mining; Set (abstract data type); World Wide Web; Artificial intelligence; MEDLINE","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":[0.02689681,0.00194769,0.01128484,0.02088622,0.001316268,0.005013728,0.004278474,0.003047795,0.003978784],"category_scores_gemma":[0.10207,0.001533193,0.01174028,0.01992454,0.001969768,0.005948102,0.002106904,0.002003236,0.0005029955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003024533,"about_ca_system_score_gemma":0.01564173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01073132,"about_ca_topic_score_gemma":0.02514394,"domain_scores_codex":[0.9816295,0.00587116,0.006498227,0.002109475,0.003577449,0.0003142772],"domain_scores_gemma":[0.8686727,0.1132372,0.01032166,0.002211439,0.005051032,0.0005060675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0005259995,0.0002051316,0.006900297,0.6776049,0.02652795,0.0001520609,0.0006056175,0.001030801,0.0002729802,0.001081253,0.003501756,0.2815912],"study_design_scores_gemma":[0.0009009824,0.001001121,0.01983464,0.6888695,0.2357001,0.001593315,0.001688164,0.002555816,0.000846364,0.005825785,0.04075361,0.0004305578],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002580263,0.9943306,0.001464417,0.0003696372,0.00009150448,0.0003565785,0.0005002763,0.00002274325,0.0002839581],"genre_scores_gemma":[0.03436892,0.9510025,0.01164897,0.000655368,0.0001620838,0.0009328738,0.001058727,0.00001989831,0.0001505965],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.02689681,"threshold_uncertainty_score":0.1422457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006548536295449375,"score_gpt":0.2318977149309664,"score_spread":0.225349178635517,"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."}}