{"id":"W2075487780","doi":"10.1109/skg.2013.29","title":"Semantic Analysis for Keywords Based User Segmentation from Internet Data","year":2013,"lang":"en","type":"article","venue":"","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Key (lock); Component (thermodynamics); Plug-in; The Internet; Segmentation; Information retrieval; Similarity (geometry); World Wide Web; Web page; Semantic similarity; Artificial intelligence; 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":[0.001648065,0.0007157114,0.001159752,0.01107162,0.0008153361,0.001298973,0.000876071,0.0009751692,0.0009082793],"category_scores_gemma":[0.00746937,0.0002498609,0.001356222,0.006224321,0.0006417448,0.002498776,0.001296956,0.0007292447,0.0007514507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009465276,"about_ca_system_score_gemma":0.001145445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00367186,"about_ca_topic_score_gemma":0.004892263,"domain_scores_codex":[0.9977328,0.0005334804,0.0003570184,0.0004670807,0.0007062098,0.0002032977],"domain_scores_gemma":[0.9964419,0.00186113,0.0004885527,0.0004169955,0.0006264735,0.0001648751],"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":[0.00184204,0.001565668,0.0944143,0.001304425,0.0004644846,0.001078004,0.001967148,0.04714083,0.06289244,0.02551002,0.009300848,0.7525198],"study_design_scores_gemma":[0.00005260034,0.0002651294,0.03570252,0.00008768458,0.0001339132,0.0007085991,0.001226161,0.8954809,0.01925015,0.03886582,0.008133326,0.00009328609],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2742254,0.001308729,0.7074796,0.0005167496,0.00008247956,0.000522863,0.00800917,0.004747361,0.003107709],"genre_scores_gemma":[0.6540941,0.0003129944,0.3320304,0.000114232,0.0001115563,0.0004339504,0.01213299,0.0001379128,0.0006317254],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01107162,"threshold_uncertainty_score":0.008715928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04659145356278281,"score_gpt":0.2827339632047855,"score_spread":0.2361425096420027,"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."}}