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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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
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. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Big Data / Marketing / Service Science / Personalization / ID-POS data |
Paper # | IBISML2012-61 |
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Committee | IBISML |
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Conference Date | 2012/10/31(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Information-Based Induction Sciences and Machine Learning (IBISML) |
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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 |