A knowledge graph-based content selection model for data-driven text generation

被引:0
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作者
Faculty of Science and Technology, Communication University of China, Beijing [1 ]
100024, China
不详 [2 ]
100024, China
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关键词
Weather forecasting - Graphic methods - Natural language processing systems;
D O I
10.1504/IJRIS.2017.090049
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学科分类号
摘要
Content selection is a critical task for natural language generation. A novel approach based on knowledge graph is proposed. Structure data is mapping to the graph and combined with user defined knowledge. The model analyses the content selection features on the graph, and automatically learns the content selection rules. The model was evaluated in the domain of weather forecasting. Copyright © 2017 Inderscience Enterprises Ltd.
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