First Place Solution for NLPCC 2017 Shared Task Social Media User Modeling

With the popularity of mobile Internet, many social networking applications provide users with the function to share their personal information. It is of high commercial value to leverage the users' personal information such as tweets, preferences and locations for user profiling. There are two subtasks working in user profiling. Subtask one is to predict the Point-of-Interest (POI) a user will check in at. We adopted a combination of multiple approach results, including user-based collaborative filtering (CF) and social-based CF to predict the locations. Subtask two is to predict the users' gender. We divided the users into two groups, depending on whether the user has posted or not. We treat this task subtask as a classification task. Our results achieved first place in both subtasks.