一个快速的基于模板的方法来自动识别网页的主要文本内容

Dat Quoc Nguyen, D. Q. Nguyen, S. Pham, T. D. Bui
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引用次数: 9

摘要

搜索引擎已经成为在互联网上浏览信息不可或缺的工具。然而,用户经常会被来自不相关网页的冗余结果所困扰。一个原因是因为搜索引擎也会查看网页的非信息性块,如广告、导航链接等。本文通过对ContentExtractor算法的改进,提出了一种快速的FastContentExtractor算法来自动检测网页中的主要内容块。通过自动识别和存储代表网站内容块结构的模板,可以快速从网站中提取新网页的内容块。还维护了输出块的层次顺序,这保证了提取的内容块与原始内容块的顺序相同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Fast Template-Based Approach to Automatically Identify Primary Text Content of a Web Page
Search engines have become an indispensable tool for browsing information on the Internet. The user, however, is often annoyed by redundant results from irrelevant web pages. One reason is because search engines also look at non-informative blocks of web pages such as advertisement, navigation links, etc. In this paper, we propose a fast algorithm called FastContentExtractor to automatically detect main content blocks in a web page by improving the ContentExtractor algorithm. By automatically identifying and storing templates representing the structure of content blocks in a website, content blocks of a new web page from the website can be extracted quickly. The hierarchical order of the output blocks is also maintained which guarantees that the extracted content blocks are in the same order as the original ones.
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