绿色网络智能文摘算法研究

Green network automatic Abstraction algorithm

随着Internet的迅猛发展,我国网民的数量激增,传统的自动文摘算法无法适应绿色网络提供优质内容并过滤不良内容的社会需求。不同于传统采用统计学习自动文摘算法,提出一种新的基于明确语义的算法,利用基于行为分析的绿色网络系统的云数据采集库和维基百科资源作为知识库建立概念空间,对该空间的词语进行语义解释。最后,实验结果证明,所提方法比传统算法用更少的句子即可以获得更高的信息覆盖率,从而大大缩短系统分析过滤不良内容的时间,提升软件的服务质量。

With the rapid development of Internet,the traditional automatic Abstraction algorithm cannot meet the needs of the green network.Different from the traditional automatic Abstraction algorithm based on statistical learning,this paper proposed a new algorithm based on clear semantics.It made use of cloud data acquisition library of green network system based on behavior analysis and Wikipedia resources as the knowledge base to establish the concept of space,it performed semantic interpretation on these words.Finally,the experimental results prove that the proposed method can cover more information with fewer sentences compared with the traditional algorithm,thus it greatly shortens the time for the system to analyze and filter inappropriate content and enhances the quality of software services.