DeepAI AI Chat
Log In Sign Up

Modeling Complementary Products and Customer Preferences with Context Knowledge for Online Recommendation

03/16/2019
by   Da Xu, et al.
WALMART LABS
0

Modeling item complementariness and user preferences from purchase data is essential for learning good representations of products and customers, which empowers the modern personalized recommender system for Walmart's e-commerce platform. The intrinsic complementary relationship among products captures the buy-also-buy patterns and provides great sources for recommendations. Product complementary patterns, though often reflected by population purchase behaviors, are not separable from customer-specific bias in purchase data. We propose a unified model with Bayesian network structure that takes account of both factors. In the meantime, we merge the contextual knowledge of both products and customers into their representations. We also use the dual product embeddings to capture the intrinsic properties of complementariness, such as asymmetry. The separating hyperplane theory sheds light on the geometric interpretation of using the additional embedding. We conduct extensive evaluations on our model before final production, and propose a novel ranking criterion based on product and customer embeddings. Our method compares favorably to existing approaches in various offline and online testings, and case studies demonstrate the advantage and usefulness of the dual product embeddings as well as the user embeddings.

READ FULL TEXT
06/28/2019

One Embedding To Do Them All

Online shopping caters to the needs of millions of users daily. Search, ...
11/18/2022

Recommending Related Products Using Graph Neural Networks in Directed Graphs

Related product recommendation (RPR) is pivotal to the success of any e-...
10/25/2019

Data Preprocessing for Evaluation of Recommendation Models in E-Commerce

E-commerce businesses employ recommender models to assist in identifying...
08/10/2022

Identifying Substitute and Complementary Products for Assortment Optimization with Cleora Embeddings

Recent years brought an increasing interest in the application of machin...
11/04/2022

A Transformer-Based Substitute Recommendation Model Incorporating Weakly Supervised Customer Behavior Data

The substitute-based recommendation is widely used in E-commerce to prov...
12/09/2022

Towards High-Order Complementary Recommendation via Logical Reasoning Network

Complementary recommendation gains increasing attention in e-commerce si...