Dongjie Zhu1, Yuhua Wang1, Chuiju You2,*, Jinming Qiu2,3, Ning Cao2, Chenjing Gong4, Guohua Yang5, Helen Min Zhou6
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1105-1115, 2019, DOI:10.32604/cmc.2019.06041
Abstract With the rapid development of the mobile Internet, users generate massive data in different forms in social network every day, and different characteristics of users are reflected by these social media data. How to integrate multiple heterogeneous information and establish user profiles from multiple perspectives plays an important role in providing personalized services, marketing, and recommendation systems. In this paper, we propose Multi-source & Multi-task Learning for User Profiles in Social Network which integrates multiple social data sources and contains a multi-task learning framework to simultaneously predict various attributes of a user. Firstly, we design their own feature extraction models… More >
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