Classification and Learning-to-rank Approaches for Cross-Device Matching at CIKM Cup 2016
This addresses cross-device matching for online advertising, but it is incremental as it applies existing techniques to a specific competition dataset.
The paper tackled cross-device matching for online advertising by proposing classification and learning-to-rank methods, with the ranking-based approach outperforming the classification-based one in the CIKM Cup 2016 competition.
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.