# Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction

## TL;DR

This paper presents an industrial solution for long sequential user behavior modeling in CTR prediction, co-designing algorithms and systems to handle thousands of behaviors efficiently, and successfully deploying it in Alibaba's advertising system.

## Contribution

It introduces a co-designed machine learning and system solution that enables handling unlimited-length user behavior sequences for CTR prediction.

## Key findings

- Handles sequences with thousands of behaviors.
- Achieves a balance between model performance and system efficiency.
- Successfully deployed in Alibaba's display advertising system.

## Abstract

Click-through rate (CTR) prediction is critical for industrial applications such as recommender system and online advertising. Practically, it plays an important role for CTR modeling in these applications by mining user interest from rich historical behavior data. Driven by the development of deep learning, deep CTR models with ingeniously designed architecture for user interest modeling have been proposed, bringing remarkable improvement of model performance over offline metric.However, great efforts are needed to deploy these complex models to online serving system for realtime inference, facing massive traffic request. Things turn to be more difficult when it comes to long sequential user behavior data, as the system latency and storage cost increase approximately linearly with the length of user behavior sequence. In this paper, we face directly the challenge of long sequential user behavior modeling and introduce our hands-on practice with the co-design of machine learning algorithm and online serving system for CTR prediction task. Theoretically, the co-design solution of UIC and MIMN enables us to handle the user interest modeling with unlimited length of sequential behavior data. Comparison between model performance and system efficiency proves the effectiveness of proposed solution. To our knowledge, this is one of the first industrial solutions that are capable of handling long sequential user behavior data with length scaling up to thousands. It now has been deployed in the display advertising system in Alibaba.