Purchase prediction via machine learning in mobile commerce

Abstract

In this paper, we propose a machine learning approach to solve the purchase prediction task launched by the Alibaba Group. In detail, we treat this task as a binary classification problem and explore five kinds of features to learn potential model of the influence of historical behaviors. These features include user quality, item quality, category quality, user-item interaction and user-category interaction. Due to the nature of mobile platform, time factor and spacial factor are considered specially. Our approach ranks the 26th place among 7186 teams in this task.