一种从Web片段中提取社会网络的方法
A Methodology to Extract Social Network from the Web Snippet
摘要：
Web已经被选为一个基本的基础设施，以获得社会结构信息，通过社会网络提取，来自世界各地。然而，大多数Web文档是非结构化的，缺乏语义。此外，网络会受到各种变化和动态的影响，由于Web包含大量节点和链接，网络可能非常复杂。在本文中，我们讨论了一种方法，这意味着协助提取和建模的社会网络的Web片段。由于手工抽取Web文档的社会网络不切实际且不具有可扩展性，而全自动抽取还处于起步阶段，因此本文提出了一种基于表面方法的（半）自动抽取方法。
英文摘要：
The Web has been chosen as a basic infrastructure to gain the social structure information, through the social network extraction, from all over the world. However, most of the web documents are unstructured and lack of semantics. Moreover, that network is subject to all kinds of changes and dynamics, and a network can be very complex due to the large number of nodes and links Web contains. In this paper, we discuss a methodology that meant to assists in extracting and modeling the social network from Web snippet. As the manual social network extraction of web documents is impractical and unscalable, and fully automated extraction are still at the very early stage to be implemented, we proposed a (semi)-automatic extraction based on the superficial methods.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
