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| Visualizing Policy Texts Based on Multi-View Collaboration |
Yanan Yang1,3( ),Wenhui Zhao2,Jian Zhang1,3,Shen Tan1,3,Beibei Zhang1,3 |
1(School of Economics and Management, Beijing University of Information Science and Technology, Beijing 100192, China)
2(School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China)
3(Beijing Key Laboratory of Big Data Decision Making for Green Development, Beijing 100192, China) |
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Abstract [Objective] This paper visualizes the text mining process through multi-view collaborative technique, aiming to identify the patterns and insights more effectively. [Methods] Based on the textual word vector matrix, we processed the texts of multi-policy subjects with data cleaning, TF-IDF calculation, vector space model, singular value decomposition and other methods. [Results] We examined effectivenesss of the proposed model with governmental information from Zhongguancun of Beijing during the period of January 2016 to August 2017. [Limitations] The framework could not visualize the single data points of large-scale texts. [Conclusions] Multi-view collaborative visualization is an effective way to interpretate text message.
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Received: 25 July 2018
Published: 15 August 2019
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