JOURNAL ARTICLE

Web-Based Dynamic Multi-Document Summarization System Framework

Meiling LiuHonge RenYu YangDequan ZhengTiejun Zhao

Year: 2013 Journal:   Journal of Software Vol: 24 (5)Pages: 1006-1021   Publisher: Science Press

Abstract

PDF HTML阅读 XML下载 导出引用 引用提醒 基于网络的动态多文档文摘系统框架 DOI: 10.3724/SP.J.1001.2013.04252 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金(60736014, 60773069, 61073130); 国家林业行业专项(201204715) Web-Based Dynamic Multi-Document Summarization System Framework Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:在自然语言处理和计算语言学相关技术支撑下,研究基于网络的动态多文档文摘系统框架,重点描述动态多文档文摘系统框架的相关内容,介绍利用矩阵子空间方法进行动态演化建模,利用相似度和质心整体优选计算方法进行信息过滤,并利用动态流形排序方法进行句子加权的动态多文档文摘生成系统.按照多文档文摘生成步骤的划分,对3 种创新的模型方法进行融合,综合起来从不同侧重点考虑,形成互补,提高系统性能.在网络环境下,此框架保证了动态演化的多文档文摘具有较高的信息新颖性和历史信息的演化性. Abstract: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. 参考文献 相似文献 引证文献

Keywords:
Automatic summarization Computer science Multi-document summarization Information retrieval XML Centroid The Internet Data mining Artificial intelligence World Wide Web

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Topics

Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence

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