MiNet: Mixed Interest Network for Cross-Domain Click-Through Rate Prediction

TL;DR

MiNet is a novel neural network model that leverages cross-domain user interests from news and ads to improve click-through rate prediction, demonstrating significant offline and online performance gains in a large-scale real-world system.

Contribution

The paper introduces MiNet, a new model that jointly captures long-term and short-term user interests across domains for enhanced CTR prediction.

Findings

MiNet outperforms state-of-the-art CTR models in offline tests.

Deployment of MiNet in UC Toutiao increases online CTR significantly.

MiNet effectively integrates multi-level attention mechanisms for interest modeling.

Abstract

Click-through rate (CTR) prediction is a critical task in online advertising systems. Existing works mainly address the single-domain CTR prediction problem and model aspects such as feature interaction, user behavior history and contextual information. Nevertheless, ads are usually displayed with natural content, which offers an opportunity for cross-domain CTR prediction. In this paper, we address this problem and leverage auxiliary data from a source domain to improve the CTR prediction performance of a target domain. Our study is based on UC Toutiao (a news feed service integrated with the UC Browser App, serving hundreds of millions of users daily), where the source domain is the news and the target domain is the ad. In order to effectively leverage news data for predicting CTRs of ads, we propose the Mixed Interest Network (MiNet) which jointly models three types of user interest: 1) long-term interest across domains, 2) short-term interest from the source domain and 3) short-term interest in the target domain. MiNet contains two levels of attentions, where the item-level attention can adaptively distill useful information from clicked news / ads and the interest-level attention can adaptively fuse different interest representations. Offline experiments show that MiNet outperforms several state-of-the-art methods for CTR prediction. We have deployed MiNet in UC Toutiao and the A/B test results show that the online CTR is also improved substantially. MiNet now serves the main ad traffic in UC Toutiao.