# Classification and Learning-to-rank Approaches for Cross-Device Matching at CIKM Cup 2016

arXiv: https://arxiv.org/abs/1612.07117 · HTML: https://mlsanity.com/paper/1612.07117/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Dec 2016.

## Built on by (most cited first, 1 of 1)

- [Multi-view user representation learning for user matching without personal information](https://mlsanity.com/paper/2312.14533/) (2023)

## Abstract (arXiv)

In this paper, we propose two methods for tackling the problem of cross-device matching for online advertising at CIKM Cup 2016. The first method considers the matching problem as a binary classification task and solve it by utilizing ensemble learning techniques. The second method defines the matching problem as a ranking task and effectively solve it with using learning-to-rank algorithms. The results show that the proposed methods obtain promising results, in which the ranking-based method outperforms the classification-based method for the task.