{"id":"W2040963032","doi":"10.1142/s0219649211002973","title":"Effectiveness of Heuristic Based Approach on the Performance of Indexing and Clustering of High Dimensional Data","year":2011,"lang":"en","type":"article","venue":"Journal of Information & Knowledge Management","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Cluster analysis; Computer science; Search engine indexing; Data mining; Curse of dimensionality; Hierarchical clustering; DBSCAN; Dimensionality reduction; Clustering high-dimensional data; Heuristic; CURE data clustering algorithm; Correlation clustering; Machine learning; Artificial intelligence","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":[0.004390808,0.0009709478,0.00131657,0.001912559,0.0009720817,0.00251492,0.002032923,0.001568273,0.001622575],"category_scores_gemma":[0.0151425,0.0004452225,0.0006088553,0.002208573,0.0009558503,0.001593124,0.0007751698,0.0008805781,0.0006705119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001878742,"about_ca_system_score_gemma":0.002415464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005739831,"about_ca_topic_score_gemma":0.004988689,"domain_scores_codex":[0.9934737,0.001717529,0.0004023441,0.0008458412,0.003114246,0.0004462886],"domain_scores_gemma":[0.9902349,0.005802547,0.0007574222,0.00125632,0.001734461,0.0002145311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002119396,0.001003528,0.009805784,0.0007813816,0.0003538473,0.0002529034,0.0003531831,0.5609009,0.02912876,0.009925558,0.005444438,0.3799304],"study_design_scores_gemma":[0.000101491,0.0005296602,0.003693999,0.00004533592,0.00006858856,0.0002286674,0.0001467467,0.9725337,0.01601159,0.003495127,0.003091945,0.00005321005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5142997,0.007109352,0.4346215,0.001054649,0.0005202477,0.0003885241,0.0005330834,0.008743626,0.03272929],"genre_scores_gemma":[0.7531117,0.0006905185,0.2431791,0.0002223444,0.00007076163,0.0001315215,0.0005831626,0.0003475127,0.001663473],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.005739831,"threshold_uncertainty_score":0.02322108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04405171062011411,"score_gpt":0.2708279659291963,"score_spread":0.2267762553090822,"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."}}