# Siamese Cookie Embedding Networks for Cross-Device User Matching

arXiv: https://arxiv.org/abs/1803.10450 · HTML: https://mlsanity.com/paper/1803.10450/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Mar 2018.

## Built on by (most cited first, 2 of 2)

- [Hierarchical Graph Neural Network with Cross-Attention for Cross-Device User Matching](https://mlsanity.com/paper/2304.03215/) (2023)
- [Multi-view user representation learning for user matching without personal information](https://mlsanity.com/paper/2312.14533/) (2023)

## Abstract (arXiv)

Over the last decade, the number of devices per person has increased substantially. This poses a challenge for cookie-based personalization applications, such as online search and advertising, as it narrows the personalization signal to a single device environment. A key task is to find which cookies belong to the same person to recover a complete cross-device user journey. Recent work on the topic has shown the benefits of using unsupervised embeddings learned on user event sequences. In this paper, we extend this approach to a supervised setting and introduce the Siamese Cookie Embedding Network (SCEmNet), a siamese convolutional architecture that leverages the multi-modal aspect of sequences, and show significant improvement over the state-of-the-art.