College of Information and Computer Engineering, Northeast Forestry University, Harbin 150001, China;Ministry of Education-Microsoft Key Laboratory of Speech Language (Harbin Institute of Technology), Harbin 150001, China 在期刊界中查找 在百度中查找 在本站中查找
This paper introduces an Internet-based dynamic multi-document summarization system to support natural language processing and computational linguistics-related technical. This paper focuses on the description of the relevant content of dynamic multi-document summarization system framework and introduces dynamic evolutionary modeling using the matrix sub-space method, the information filtering model that uses the similarity and centroid integer selection method, and weighted sentence sorting, using the dynamic manifold method to generate the dynamic multi-document summarization system. This paper fuses the three innovation modeling methods to complement and to improve the performance of the system in accordance with the division of generated step of multi-document summarization. In a network environment, the framework ensures the dynamic evolutionary multi-document summarization with high novel information and evolutionary historical information.
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