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

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摘要 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.
出处 《Data Intelligence》 2019年第2期160-175,共16页 数据智能(英文)
基金 This work is partially supported by the National Natural Science Foundation of China(Grant numbers:61502115,61602326,U1636103 and U1536207) the Fundamental Research Fund for the Central Universities(Grant numbers:3262017T12,3262017T18,3262018T02 and 3262018T58).
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