A Generalized Links and Text Properties Based Forum Crawler

Amit Sachan, Wee-Yong Lim, V. Thing
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引用次数: 10

Abstract

Web forums have become a major source of information gathering/mining due to a large amount of user generated content. Crawling of web forums is necessary to gather/mine the information from them. However, a generic web crawler is unable to efficiently and effectively crawl the web forums because of the existence of many redundant and duplicate pages. In addition, there exists a crawling relationship among the useful pages that need to be considered. So, for efficient crawling, we need to intelligently crawl the web forums by eliminating redundant and duplicate pages, and understanding the crawling relationship. Existing works in forum crawling use visual pattern recognition based methods, which make them extremely computational expensive. In this paper, we propose a novel light-weight crawling method using text and links properties of the pages in web forums. Theoretical analysis and experimental results show the effectiveness and efficiency of the proposed method.
一个基于链接和文本属性的论坛爬虫
由于大量的用户生成内容,网络论坛已经成为信息收集/挖掘的主要来源。爬行网络论坛是必要的,以收集/挖掘他们的信息。然而,由于存在许多冗余和重复的网页,一般的网络爬虫无法高效和有效地抓取网络论坛。此外,需要考虑的有用页面之间存在爬行关系。因此,为了实现高效的抓取,我们需要通过消除冗余和重复的页面来智能地抓取论坛,并理解抓取关系。现有的论坛爬行工作使用基于视觉模式识别的方法,这使得它们的计算成本非常高。本文提出了一种基于论坛页面的文本和链接属性的轻量级抓取方法。理论分析和实验结果表明了该方法的有效性和高效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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