{"id":"W3141059875","doi":"10.1007/s10618-005-1355-x","title":"Mining Customer Value: From Association Rules to Direct Marketing","year":2005,"lang":"en","type":"article","venue":"Data Mining and Knowledge Discovery","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":117,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Association rule learning; Profit (economics); Computer science; Data mining; Liberian dollar; Direct marketing; Customer lifetime value; Customer value; Marketing; Artificial intelligence; Machine learning; Customer retention; Business; Economics; Finance","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":[0.002088039,0.001116155,0.001299176,0.008165473,0.0007216602,0.00251613,0.001782368,0.001437195,0.001282103],"category_scores_gemma":[0.01577572,0.0005571874,0.001514751,0.00614301,0.0006588196,0.002311364,0.001033445,0.001928946,0.001094354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005341206,"about_ca_system_score_gemma":0.001046857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004753905,"about_ca_topic_score_gemma":0.005938932,"domain_scores_codex":[0.9979576,0.0005599029,0.0002079485,0.0004626282,0.0006711259,0.0001408293],"domain_scores_gemma":[0.9871471,0.01054532,0.0006706488,0.0006104533,0.0007965648,0.0002300155],"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":[0.0008967638,0.002187593,0.1941845,0.0005765673,0.001283958,0.001514114,0.0005800849,0.03053873,0.003435023,0.005766421,0.01333312,0.7457032],"study_design_scores_gemma":[0.0002877536,0.000522409,0.06043594,0.000324012,0.001650183,0.002157105,0.001089938,0.8033013,0.008595553,0.1095497,0.01197229,0.0001137416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7287794,0.00789167,0.2405359,0.003062147,0.0003329052,0.0004379136,0.008463337,0.002633769,0.007862872],"genre_scores_gemma":[0.8699178,0.001703076,0.1156029,0.0003999568,0.0003359499,0.0002374785,0.009897125,0.0000994978,0.001806039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008165473,"threshold_uncertainty_score":0.01104271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03081130680570864,"score_gpt":0.2724500237614445,"score_spread":0.2416387169557359,"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."}}