Presentation 2012-11-07
Purchase Behavior Modeling by Latent Class Introduced Hierarchical Bayes Probit Model
Tsukasa ISHIGKI, Nobuhiko TERUI, Tadahiko SATO,
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Abstract(in English) This report describes a marketing model for personalization by using a large-scale transaction dataset in retail service. Our approach aims to combine a hierarchical Bayes binary probit model and latent class model to deal with a large-scale customers and products. The model is capable of estimation of response coefficients associated with marketing variables for each customers and products.
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Keyword(in English) Big Data / Marketing / Service Science / Personalization / ID-POS data
Paper # IBISML2012-61
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Committee IBISML
Conference Date 2012/10/31(1days)
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Registration To Information-Based Induction Sciences and Machine Learning (IBISML)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Purchase Behavior Modeling by Latent Class Introduced Hierarchical Bayes Probit Model
Sub Title (in English)
Keyword(1) Big Data
Keyword(2) Marketing
Keyword(3) Service Science
Keyword(4) Personalization
Keyword(5) ID-POS data
1st Author's Name Tsukasa ISHIGKI
1st Author's Affiliation Graduate School of Economics and Management, Tohoku University()
2nd Author's Name Nobuhiko TERUI
2nd Author's Affiliation Graduate School of Economics and Management, Tohoku University
3rd Author's Name Tadahiko SATO
3rd Author's Affiliation Graduate School of Business Science, University of Tsukuba
Date 2012-11-07
Paper # IBISML2012-61
Volume (vol) vol.112
Number (no) 279
Page pp.pp.-
#Pages 6
Date of Issue