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

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 extra...

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Bibliographic Details
Published in:Data intelligence 2019-04, Vol.1 (2), p.160-175
Main Authors: Lu, Junru, Chen, Le, Meng, Kongming, Wang, Fengyi, Xiang, Jun, Chen, Nuo, Han, Xu, Li, Binyang
Format: Article
Language:English
Subjects:
Artificial neural networks
Blogs
Convolutional neural network (CNN)
Datasets
Information science
International relations
Keyword extraction
Keywords
Labeling
Neural networks
Self-attention
Social networks
Software
Technology assessment
User behavior
User generated content
User profile
User profiles
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Summary: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.
ISSN:2641-435X
2641-435X
DOI:10.1162/dint_a_00009