[1E4-GS-9] Natural language processing, information retrieval: Text mining

[1E4-GS-9-04] Improving product search by multi-task learning using access log

〇Hitoshi Shimizu¹, Tomoharu Iwata¹ (1. NTT Cmmunication Science Laboratories)

Keywords:Information retrieval

The ranking of product search results displayed to users has a significant effect on sales of an E-Commerce website.

We propose a method to improve product search using access logs.

Using features obtained from products and queries and access logs as learning data, a neural network is trained to display frequently accessed products at high rank.

There are multiple types of access logs, such as not only conversions, but also carts and clicks.

We experimentally confirmed that training data other than the target type can improve learning to rank.