{"id":"W4317042660","doi":"10.1145/3578708","title":"Fast and Accurate Framework for Ontology Matching in Web of Things","year":2023,"lang":"en","type":"article","venue":"ACM Transactions on Asian and Low-Resource Language Information Processing","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brandon University","funders":"","keywords":"Computer science; Cluster analysis; Ontology; Data mining; Information retrieval; Matching (statistics); Web of Things; Semantic Web; Interoperability; The Internet; Artificial intelligence; World Wide Web; Mathematics","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":[0.003278491,0.001028047,0.00172139,0.005120692,0.001757831,0.003738346,0.003214529,0.001853092,0.002302799],"category_scores_gemma":[0.01032018,0.0008794218,0.003017175,0.005334978,0.001199589,0.006707398,0.004923148,0.002348175,0.001892663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002276333,"about_ca_system_score_gemma":0.003334239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01179456,"about_ca_topic_score_gemma":0.01156001,"domain_scores_codex":[0.9956631,0.0008230255,0.0003807539,0.000753813,0.002072427,0.0003068607],"domain_scores_gemma":[0.9979873,0.0005397334,0.0002460144,0.0006015946,0.0005278661,0.00009745656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009560771,0.000147996,0.00225123,0.0004890126,0.0002096038,0.0008174389,0.0004232922,0.2328771,0.005368408,0.4747913,0.01271783,0.2698112],"study_design_scores_gemma":[0.00001114351,0.00002235242,0.0003524314,0.00006158086,0.00003172506,0.0002750939,0.0001585228,0.824606,0.001932617,0.152584,0.01992791,0.00003668146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009845404,0.0001879625,0.9969819,0.0001252605,0.00003697056,0.00009150694,0.0001344415,0.0006057559,0.000851684],"genre_scores_gemma":[0.06290907,0.0007552626,0.9325481,0.0001068079,0.00007010921,0.0003005608,0.001398246,0.0001463951,0.001765362],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01179456,"threshold_uncertainty_score":0.02345181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204690886698901,"score_gpt":0.2703067519801377,"score_spread":0.2582598431131487,"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."}}