Xuan Truong Dinh
ABSTRACT
In the recent years, there are huge data extracted from social networks in both static and real-time analysis, such as Facebook, Twitter, LinkedIn, and Instagram. Recently, most researchers have investigated in classifying textual contents without user interests/behaviors from huge data of social networks. This paper has presented a novel approach using a Convolution Neural Network with its new contribution of user perceptions from the social network data to classifying the user interests. Experimental results show that the proposed model performs better than the conventional algorithms in terms of classifying user interests. Additionally, the proposed model enhances a quality of classification for user interests tracking real-time in social networks.
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Index Terms
- A Proposal of Deep Learning Model for Classifying User Interests on Social Networks
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