Xiaodong Wang
ABSTRACT
In recent years, big data has become the new focus of attention from all walks of life. The valuable information contained in big data becomes the driving force for people to process and analyze big data. Big data analytics helps enterprises to take better decisions to improve business output. As a user description tool, user profile is widely used in various fields. However, it is difficult to deal with large-scale datasets using traditional methods since the established processes was not designed to handle large volumes of data. In this paper, we propose a user profile analysis framework using machine learning approach which apply advanced machine learning programs to solve industrial scale problems. And this approach can be effective to speculate real and potential needs of various groups of users and precisely extract individual characteristics and group generality. By introducing high-level data parallel framework, the process of large-scale data processing can be executed efficiently. We use real-world data to validate the effectiveness of the proposed framework.
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Index Terms
- A User Profile Analysis Framework Driven by Distributed Machine Learning for Big Data
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