Recovering Cross-Device Connections via Mining IP Footprints with Ensemble Learning

Abstract

This paper describes our solution to ICDM 2015's contest. The challenge is to recover cross-device connections, i.e. identifying device-cookie pairs that is used by the same natural person. To tackle this task, we first model the privateness of each IP, then employ pairwise ranking techniques for predicting the likelihood of each connection, finally ensemble learning is used for integrating multiple models from various settings. Our approach achieves 5th place in the contest (average F-score of 0.8608) using ONLY IP footprint information.