Towards intelligent policy analysis: A discourse structure parsing technique for Chinese government document |
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| Institution: | 1. Department of Information Management, Dongbei University of Finance & Economics, Dalian, Liaoning, China;2. Department of Information Resources Management, Business School of Nankai University, Tianjin, China;3. Center for Network Society Governance of Nankai University, Tianjin, China;1. School of Management, Huazhong University of Science and Technology, Wuhan 430074, China;2. Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China;3. Tippie College of Business, The University of Iowa, Iowa City, IA 52242, United States of America;4. School of Business, Sun Yat-sen University, Guangzhou 510275, China |
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| Abstract: | Government document analysis can help organizations to understand key policy points and make right response. To realize intelligent analysis of a volume of policies, we propose a discourse parsing technique for in-depth understanding of Chinese government documents (CGDs). Based on Superstructure Schema and Rhetorical Structure Theory (RST), we characterize the stylistic features and macrostructure patterns of CGDs and develop a discourse analysis framework to specify its functional structure and semantic system. A tree schema is adopted to portray the hierarchy of textual fragments in full text and formalize their representations in machine-based parsing, then a multi-head partition self-attention model is constructed to evaluate the discourse analysis framework. Experiment results show that our parsing model embedding with inherent CGD discourse features performs better than baselines. The highest f1-score in span and label prediction tasks researches 0.9209. The parsing model can be migrated to other discourse parsing tasks by considering specific genre features of different documents. |
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