混合聚焦网络爬虫的框架

Yixue Sun, Peiquan Jin, Lihua Yue
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引用次数: 20

摘要

由于Web结构复杂,大多数集中爬行方法采用局部搜索算法,该算法只搜索Web子图中的页面。Web页面的多主题特性使得很难确定Web页面与给定主题的相关性。针对这两个问题,本文提出了一种新的基于元搜索和VIPS(基于视觉的页面分割)算法的混合聚焦爬行方法。我们使用元搜索来实现比传统的局部搜索算法更大的爬行范围。此外,为了获得更好的查全率和查准率,我们采用基于vips的算法对网页进行相关性计算,该算法首先将网页划分为一组反映页面语义结构的块。在简要回顾了相关工作的基础上,讨论了混合聚焦爬行器的系统架构,并给出了混合聚焦爬行方法的框架。
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A Framework of a Hybrid Focused Web Crawler
Because of the complex Web structure, most approaches of focused crawling employ a local search algorithm, which will only search pages in a sub-graph of the Web. And the multi-topic feature of Web pages makes it difficult to determine the relevance of a Web page to a given topic. Towards those two issues, in this paper we present a new hybrid approach to focused crawling, which is based on meta-search and VIPS (VIsion based Page Segmentation) algorithm. We use meta-search to achieve a wider crawling range than traditional local search algorithm. Besides, in order to obtain better recall and precision, we use VIPS-based algorithm for the relevance computation of a Web page, which first partitions a Web page into a set of blocks that reflect the semantic structure of the page. The system architecture of hybrid focused crawler is discussed after a short review on related work, and then we present the framework of the hybrid focused crawling approach.
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