给同一个session的items构建一个bundle graph，同时利用item的特征，构建graph中物品之间的关系。最后把这种设想，基于主题模型式的生成模型进行刻画（细节还不太了解），不过这种构图模式可以解决。
| 文献题目 | 去谷歌学术搜索 | ||||||||||
| Modeling Buying Motives for Personalized Product Bundle Recommendation | |||||||||||
| 文献作者 | HUI XIONG | ||||||||||
| 文献发表年限 | 2017 | ||||||||||
| 文献关键字 | |||||||||||
| 主题模型；生成模型；解释；利用物品特征和集合关系构造物品之间的联系；构图模式 | |||||||||||
| 摘要描述 | |||||||||||
| Product bundling is a marketing strategy that offers several products/items for sale as one bundle. While the bundling strategy has been widely used, less efforts have been made to understand how items should be bundled with respect to consumers’ preferences and buying motives for product bundles. This article investigates the relationships between the items that are bought together within a product bundle. To that end, each purchased product bundle is formulated as a bundle graph with items as nodes and the associations between pairs of items in the bundle as edges. The relationships between items can be analyzed by the formation of edges in bundle graphs, which can be attributed to the associations of feature aspects. Then, a probabilistic model BPM (Bundle Purchases with Motives) is proposed to capture the composition of each bundle graph, with two latent factors node-type and edge-type introduced to describe the feature aspects and relationships respectively. Furthermore, based on the preferences inferred from the model, an approach for recommending items to form product bundles is developed by estimating the probability that a consumer would buy an associative item together with the item already bought in the shopping cart. Finally, experimental results on real-world transaction data collected from well-known shopping sites show the effectiveness advantages of the proposed approach over other baseline methods. Moreover, the experiments also show that the proposed model can explain consumers’ buying motives for product bundles in terms of different node-types and edge-types | |||||||||||
