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引用次数: 0

摘要

监督的网络规模的论坛爬虫是从网络抓取相关的论坛内容与最小的开销。论坛线程所包含的信息内容是论坛爬虫的目标,每个论坛都有不同的布局或风格,也有不同的论坛软件包,它们总是有相似的恒定导航路径,通过特定的URL类型连接,将用户从入口页面引导到线程页面,我们将web论坛的爬行问题减少为URL类型识别问题。并展示了如何使用来自弱页面类型分类器的聚合结果从自动创建的训练集中学习准确有效的固定导航路径正则表达式模式。健壮的页面类型分类器可以从五个带注释的论坛中体验到,并应用于大量未见过的论坛。结果表明,Focus在由150多个不同的论坛软件包支持的大型测试论坛上实现了超过98%的有效性和97%的覆盖率。将Focus应用于100多个社区的结果表明,持续导航路径的概念可以应用于其他社交媒体网站。
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Crawling the page flipping links
The supervised web-scale forum crawler is to crawl relevant forum content from the web with minimum overhead. Forum threads contain information content that is the target of forum crawlers, each forums have different layouts or styles and have different forum software packages, they always have similar constant navigation paths connected by specific URL types to direct users from entry pages to thread page, we reduce the web forum crawling problem to a URL-type recognition problem. And shows how to learn accurate and effective regular expression patterns of constant navigation paths from automatically created training sets using aggregated results from weak page type classifiers. Robust page type classifiers can be experienced from as few as five annotated forums and applied to a large set of unseen forums. The results show that Focus achieved over 98 percent effectiveness and 97 percent coverage on a large set of test forums powered by over 150 different forum software packages., The results of applying Focus on more than 100 community, the concept of constant navigation path could apply to other social media site.
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