{"id":"W2112550212","doi":"10.1109/wicom.2011.6040596","title":"Similar Web Services Discovery and Matching Based on P2P and Topic Model Learning","year":2011,"lang":"en","type":"article","venue":"","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centro Nacional de Investigaciones Cardiovasculares; Heart and Stroke Foundation of Canada","keywords":"Computer science; Web service; Overlay; Matching (statistics); Locality; Information retrieval; World Wide Web; Hilbert curve; Overlay network; Service discovery; WS-Policy; Service (business); Data mining; The Internet; Web application security; Web development; Algorithm; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002483283,0.0006336307,0.001790886,0.00435503,0.001655461,0.002578099,0.002348024,0.0015206,0.002049109],"category_scores_gemma":[0.008188975,0.0005033085,0.001379711,0.005592916,0.0008694751,0.004869397,0.002980022,0.001216387,0.001218988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001417511,"about_ca_system_score_gemma":0.002021178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00824395,"about_ca_topic_score_gemma":0.006157869,"domain_scores_codex":[0.9968269,0.0008104202,0.0001933374,0.0007798754,0.001173578,0.0002157682],"domain_scores_gemma":[0.9970605,0.001037895,0.0002261848,0.0009975515,0.0004957561,0.0001821169],"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":[0.0006556457,0.0006404699,0.007510989,0.0003193825,0.000383965,0.0005667145,0.0007438829,0.08797287,0.02226175,0.06763506,0.008653483,0.8026558],"study_design_scores_gemma":[0.00003864784,0.00005198186,0.0007674769,0.000007182515,0.00005840338,0.000281,0.00008979587,0.9538562,0.01033769,0.02952363,0.004945004,0.00004307073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01309837,0.0001480414,0.9818459,0.0001438714,0.00002247153,0.0001517909,0.0001079803,0.003305775,0.00117573],"genre_scores_gemma":[0.318807,0.0002624071,0.6764299,0.0001419433,0.00008921408,0.0002828651,0.0008683456,0.0002711772,0.002847127],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00824395,"threshold_uncertainty_score":0.01639193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.010497265211423,"score_gpt":0.1959642268374839,"score_spread":0.1854669616260609,"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."}}