Meteorological Bulletin Automatic Generation based on Spatio-Temporal Reasoning

Hua-Ping Zhang,Huan-Ping Wu,Jian Gao,Yan-Ping Zhao,Zhong-Liang Lv,Meteorological Bulletin Automatic Generation based on Spatio-Temporal Reasoning,In Proceedings of 2011 International Conference on Machine Learning and Cybernetics in Guangxi, China,2011.7,p1927-1931



Abstract


Meteorological bulletin has more and more diversified, large scale, highly integrated requirements and potential demands from whole society. The strong professional efforts involved in transforming the variety of special meteorological data to natural language text are becoming more challenging in providing sophisticated and easily understood weather features. This paper presents a new Meteorological bulletin automatic generation method based on spatio-temporal reasoning. To enhance an exact and non-redundant description for complex meteorological data, and for special future tendency dynamics in emerged interesting areas. We also evaluate this method with real data from National Meteorological Center and prove that it’s feasible and effective after implementing.


 



 


Meteorologic Bulletin Automatic Generation based o Spatio-Temporal Reasoning0526.pdf(174 KB)

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