{"id":"W2168846201","doi":"10.1109/icdm.2008.93","title":"WiFIsViz: Effective Visualization of Frequent Itemsets","year":2008,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Visualization; Representation (politics); Data mining; Information retrieval; Association rule learning; Data visualization; Creative visualization","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":[0.001392647,0.002260264,0.001130738,0.004291035,0.0004941351,0.002169766,0.001675021,0.001359902,0.015763],"category_scores_gemma":[0.007644745,0.0006765766,0.001104019,0.002382858,0.0002888589,0.003086377,0.002676398,0.001431174,0.002347364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000269453,"about_ca_system_score_gemma":0.0004345922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0013286,"about_ca_topic_score_gemma":0.001135148,"domain_scores_codex":[0.9993219,0.000184587,0.00007850157,0.00009832996,0.0002505096,0.00006614032],"domain_scores_gemma":[0.9970386,0.00171015,0.0002605095,0.000321696,0.0004818239,0.0001872561],"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":[0.002503607,0.0002776301,0.006002569,0.002974804,0.0003844354,0.00179696,0.002583328,0.02025081,0.06460795,0.01671446,0.1827799,0.6991236],"study_design_scores_gemma":[0.001187991,0.0008075946,0.01340388,0.0008649877,0.0003604884,0.004129791,0.001167066,0.5383993,0.109533,0.05703504,0.2725239,0.0005870005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0229101,0.001202532,0.8562868,0.0009172017,0.0002842451,0.0003178455,0.01061976,0.1031487,0.004312868],"genre_scores_gemma":[0.1188928,0.00170623,0.8610197,0.0003015983,0.0001986018,0.0006718147,0.01064649,0.003816465,0.002746378],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.015763,"threshold_uncertainty_score":0.05273253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01622154738406882,"score_gpt":0.2695666566170058,"score_spread":0.253345109232937,"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."}}