An Automatic Label Extraction Technique for Domain-Specific Hidden Web Crawling (LEHW)

A. El-Desouky, H. Ali, S. El-Ghamrawy
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引用次数: 4

Abstract

General-purpose search engines (e.g. Google and Yahoo) ignore valuable data that represent 80% of the content on the Web, this portion of Web called hidden Web (HW). Pages in the hidden Web are dynamically generated in response to queries submitted via the search forms. In this paper, a new algorithm for extracting labels from multi-attribute (M-A) search form fields is proposed. A technique for automatic query generation for single-attribute (S-A) search forms is also provided in order to enhance the performance of the overall domain-specific hidden Web crawlers. The innovation of (LEHW) algorithm is its capability to distinguish between (S-A) and (M-A) forms; so that the capability of dealing with both of them, unlike most hidden Web crawlers that ignore either of them. Embedding of the proposed algorithm within the overall framework of the HW crawler is evaluated through experiments using real Web sites. The preliminary results demonstrate the accuracy and precision of the proposed approach for most of the sites considered
面向特定领域的隐式网络爬行(LEHW)自动标签提取技术
通用搜索引擎(如Google和Yahoo)忽略了有价值的数据,这些数据代表了网络上80%的内容,这部分网络被称为隐藏网络(HW)。隐藏Web中的页面是动态生成的,以响应通过搜索表单提交的查询。提出了一种从多属性搜索表单字段中提取标签的新算法。还提供了一种为单属性(S-A)搜索表单自动生成查询的技术,以增强整个特定于领域的隐藏Web爬虫的性能。(LEHW)算法的创新之处在于能够区分(S-A)和(M-A)两种形式;这样就可以同时处理它们,而不像大多数隐藏的网络爬虫会忽略它们中的任何一个。通过实际网站的实验,评估了该算法在HW爬虫整体框架中的嵌入情况。初步结果表明,对于大多数考虑的站点,所提出的方法是准确和精确的
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