{"id":"W2406750717","doi":"","title":"Frequent subgraph mining from streams of linked graph structured data","year":2015,"lang":"en","type":"article","venue":"Mspace (University of Manitoba)","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Data stream mining; Disjoint sets; Graph; Big data; Theoretical computer science; Data mining; Knowledge graph; Information retrieval; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001059963,0.0007900632,0.001012385,0.005462199,0.0006663364,0.0014272,0.001269369,0.001015764,0.0005466728],"category_scores_gemma":[0.008925575,0.0004139885,0.00113593,0.005102817,0.0003386012,0.002449706,0.001320067,0.0008752579,0.0005754026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003573936,"about_ca_system_score_gemma":0.0006904675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002253343,"about_ca_topic_score_gemma":0.004962902,"domain_scores_codex":[0.998526,0.0003784922,0.000151714,0.0003381796,0.0004666522,0.0001389598],"domain_scores_gemma":[0.9951126,0.00255222,0.0005708211,0.000725882,0.000782271,0.0002562238],"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":[0.001525417,0.00102004,0.06498486,0.001792584,0.001288209,0.004546123,0.001328653,0.1040648,0.03991049,0.02295214,0.04690614,0.7096805],"study_design_scores_gemma":[0.0001124718,0.0003111361,0.01143883,0.0001604274,0.0002992293,0.002110611,0.001074908,0.8692661,0.01421916,0.08275513,0.01818814,0.00006393009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.298741,0.004905407,0.6679152,0.001814289,0.0002793464,0.0006091765,0.01849618,0.004622207,0.002617222],"genre_scores_gemma":[0.5697424,0.002156554,0.3788376,0.0001671077,0.0002206086,0.0003436434,0.04702051,0.0002267131,0.001284902],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005462199,"threshold_uncertainty_score":0.005605698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05193318104658357,"score_gpt":0.2312774648480558,"score_spread":0.1793442838014722,"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."}}