Identifying User Profile by Incorporating Self-Attention Mechanism based on CSDN Data Set

• Main Authors: Lu, Junru, Chen, Le, Meng, Kongming, Wang, Fengyi, Xiang, Jun, Chen, Nuo, Han, Xu, Li, Binyang
• Format: Article
• Language: English
• Published: The MIT Press 2019-05-01
• Series: Data Intelligence
• Online Access: https://www.mitpressjournals.org/doi/abs/10.1162/dint_a_00009

With the popularity of social media, there has been an increasing interest in user profiling and its applications nowadays. This paper presents our system named UIR-SIST for User Profiling Technology Evaluation Campaign in SMP CUP 2017. UIR-SIST aims to complete three tasks, including keywords extraction from blogs, user interests labeling and user growth value prediction. To this end, we first extract keywords from a user's blog, including the blog itself, blogs on the same topic and other blogs published by the same user. Then a unified neural network model is constructed based on a convolutional neural network (CNN) for user interests tagging. Finally, we adopt a stacking model for predicting user growth value. We eventually receive the sixth place with evaluation scores of 0.563, 0.378 and 0.751 on the three tasks, respectively.