Web Page Content Extraction Method Based on Link Density and Statistic

Web page content extraction is a key step for knowledge acquisition from the Internet. The physical layout of Web pages is always composed of useful information, advertising links and images. So how to extract the right content and filter out irrelevant information is an important work. According to the different properties between content nodes and non-content nodes of Web page represented as a tree, an algorithm based on link density and statistic is presented. This method increases the veracity of content extraction which will benefit the efficiency of information acquirement for corporations and organizations. The work of this paper is important for knowledge acquisition.