IMPLEMENTATION OF SMARTCRAWLER FOR DEEP-WEB SITES

Ewit
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Abstract

Deep web is termed as data present on web but inaccessible to search engine. Due to the large volume of web resources and the dynamic nature of deep web, achieving wide coverage and high efficiency is a challenging issue. Smart crawler for hidden web interfaces consist of mainly two stages, first is site locating another is in-site exploring. Site locating starts from seed sites and obtains relevant websites through reverse searching and obtains relevant sites through feature space of URL, anchor and text around URL. Second stage takes input from site locating and goes to find relevant link from those sites. The adaptive link learner is used to find out relevant links with help of link priority and link rank.. To eliminate bias on visiting some highly relevant links in hidden web directories, we design a link tree data structure to achieve wider coverage for a website.
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深层网站的智能爬虫实现
深网是指存在于网络上但搜索引擎无法访问的数据。由于网络资源的巨大容量和深网的动态性,实现广覆盖和高效率是一个具有挑战性的问题。隐藏界面智能爬虫主要包括两个阶段,一是站点定位阶段,二是站点内探索阶段。网站定位从种子网站开始,通过反向搜索获得相关网站,通过URL、锚点、URL周围文字的特征空间获得相关网站。第二阶段从站点定位输入,并从这些站点找到相关链接。自适应链接学习器通过链接优先级和链接等级来寻找相关链接。为了消除访问隐藏网络目录中一些高度相关链接的偏见,我们设计了一个链接树数据结构,以实现网站的更广泛覆盖。
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