Deep Learning-based Online Alternative Product Recommendations at Scale

by   Mingming Guo, et al.

Alternative recommender systems are critical for ecommerce companies. They guide customers to explore a massive product catalog and assist customers to find the right products among an overwhelming number of options. However, it is a non-trivial task to recommend alternative products that fit customer needs. In this paper, we use both textual product information (e.g. product titles and descriptions) and customer behavior data to recommend alternative products. Our results show that the coverage of alternative products is significantly improved in offline evaluations as well as recall and precision. The final A/B test shows that our algorithm increases the conversion rate by 12 percent in a statistically significant way. In order to better capture the semantic meaning of product information, we build a Siamese Network with Bidirectional LSTM to learn product embeddings. In order to learn a similarity space that better matches the preference of real customers, we use co-compared data from historical customer behavior as labels to train the network. In addition, we use NMSLIB to accelerate the computationally expensive kNN computation for millions of products so that the alternative recommendation is able to scale across the entire catalog of a major ecommerce site.


page 1

page 2

page 3

page 4


Online Product Feature Recommendations with Interpretable Machine Learning

Product feature recommendations are critical for online customers to pur...

Dynamic Learning with Frequent New Product Launches: A Sequential Multinomial Logit Bandit Problem

Motivated by the phenomenon that companies introduce new products to kee...

Deep Recurrent Neural Networks for Product Attribute Extraction in eCommerce

Extracting accurate attribute qualities from product titles is a vital c...

Analyzing Customer Feedback for Product Fit Prediction

One of the biggest hurdles for customers when purchasing fashion online,...

Distributed Vector Representation Of Shopping Items, The Customer And Shopping Cart To Build A Three Fold Recommendation System

The main idea of this paper is to represent shopping items through vecto...

Learning to Sell a Focal-ancillary Combination

A number of products are sold in the following sequence: First a focal p...

Towards A Personal Shopper's Dilemma: Time vs Cost

Consider a customer who needs to fulfill a shopping list, and also a per...

Please sign up or login with your details

Forgot password? Click here to reset