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As the number and variety of smart devices increase, users may use myriaddevices in their daily lives and the online activities become highlyfragmented. Building an accurate user identity becomes a difficult andimportant problem for advertising companies. The task for the CIKM Cup 2016Track 1 was to find the same user cross multiple devices. This paper discussesour solution to the challenge. It is mainly comprised of three parts:comprehensive feature engineering, negative sampling, and model selection. Foreach part we describe our special steps and demonstrate how the performance isboosted. We took the second prize of the competition with an F1-score of0.41669.

Cross-Device User Matching Based on Massive Browse Logs: The Runner-Up Solution for the 2016 CIKM Cup