Linking Multi-Category Purchases to Latent Activities of Shoppers: Analysing Market Baskets by Topic Models
Linking Multi-Category Purchases to Latent Activities of Shoppers: Analysing Market Baskets by Topic Models
复制标题
将多类别购买与购物者的潜在活动联系起来:按主题模型分析市场篮子
DOI:
10.15358/0344-1369_2014_4_267
复制
发表时间:
2014
影响因子:
5
通讯作者:
H. Hruschka
中科院分区:
文献类型:
--
作者:
H. Hruschka
We investigate the application of two topic models, latent Dirichlet allocation (LDA) and the correlated topic model (CTM), to market basket analysis. Topic models measure the association between observed purchases and underlying latent activities of shoppers by conceiving each basket as random mixture of latent activities. We explain the structure of the two topic models used. We discuss estimation of LDA models by blocked Gibbs sampling. In addition we show how to evaluate the performance of topic models on estimation and holdout data. In the empirical study we analyse a total of 18,000 purchases made at a medium-sized supermarket which refer to 60 product categories. The LDA model performs better than the CTM in terms of log likelihood values. Latent activities inferred by this models are intuitive and interpretable, e.g., related to shopping of beverages or personal care, to baking or to an inclination towards luxury food. To illustrate the managerial relevance of estimated topic models we sketch the core of a recommender system which ranks purchase probabilities of other product categories conditional on the basket of a shopper.
DOI:
10.1073/pnas.0307752101
发表时间:
2004-04-06
影响因子:
11.1
作者:
Griffiths, TL;Steyvers, M
通讯作者:
Steyvers, M
DOI:
--
发表时间:
2011
期刊:
影响因子:
--
作者:
Hideo Kozumi;Genya Kobayashi;服部鮎奈;小林弦矢;小林弦矢;小林弦矢;小林弦矢;小林弦矢
通讯作者:
小林弦矢