{"id":"W1979325497","doi":"10.4018/jswis.2006070104","title":"Information Retrieval by Semantic Similarity","year":2006,"lang":"en","type":"article","venue":"International Journal on Semantic Web and Information Systems","topic":"Topic Modeling","field":"Computer Science","cited_by":228,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Semantic similarity; Computer science; Information retrieval; WordNet; Explicit semantic analysis; Semantic integration; Semantic computing; Similarity (geometry); Ontology; Vector space model; Semantic search; Natural language processing; Artificial intelligence; Semantic technology; Semantic Web; Image (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":[0.006391887,0.001549492,0.003327266,0.01664233,0.001334873,0.007466928,0.002566959,0.002950986,0.007896899],"category_scores_gemma":[0.02170737,0.0006487645,0.002246656,0.02150724,0.002684258,0.01783399,0.00558204,0.002043382,0.006432825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002584573,"about_ca_system_score_gemma":0.002059917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001639334,"about_ca_topic_score_gemma":0.001208969,"domain_scores_codex":[0.9868699,0.005352171,0.001322486,0.001569525,0.004513247,0.0003727209],"domain_scores_gemma":[0.9950129,0.002399308,0.0003832626,0.001308138,0.0007929443,0.0001033833],"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":[0.0002267436,0.0003050407,0.001364096,0.002395478,0.0005191673,0.0003362973,0.0006453901,0.015523,0.007902218,0.2790755,0.0365531,0.6551539],"study_design_scores_gemma":[0.0001498395,0.0004111536,0.001471053,0.000590718,0.0002675876,0.001396233,0.000719341,0.1519604,0.009958476,0.6972605,0.1355836,0.0002310678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01099706,0.01631831,0.9412794,0.002576612,0.0007587394,0.00146597,0.001467403,0.001903751,0.02323266],"genre_scores_gemma":[0.188049,0.02051052,0.7680677,0.001323306,0.001761771,0.001857913,0.005933134,0.0003216311,0.01217507],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01664233,"threshold_uncertainty_score":0.03380394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008796478971780134,"score_gpt":0.2300101662255508,"score_spread":0.2212136872537707,"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."}}