DeepSearcher: A Chinese deep web classified search engine

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作者
Institute of Intelligent Information Processing and Application, Soochow University, Suzhou 215006, China [1 ]
机构
来源
J. Comput. Inf. Syst. | 2008年 / 1卷 / 111-118期
关键词
Automatic classification - Back end databases - Crawlable pages - Data integration - Deep web - Domain hierarchy;
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摘要
Web search engines work well in finding crawlable pages, but not well in finding pages dynamically generated by back-end databases. These pages are often referred to as the Deep Web. According to many studies, the Deep Web reside in topic-specific back-end databases, and the size of the Deep Web increases rapidly. Moreover, contents provided by Deep Web are often of high quality and well-structured. Organizing such structured sources into a domain hierarchy will make users conveniently browse to find these valuable resources and this is one of the critical steps toward large-scale integration of heterogeneous Deep Web sources. We design a prototype of Chinese Deep Web classified search engine called DeepSearcher. We also propose a Deep Web crawling strategy and algorithm for Deep Web judgment and classification. Our experimental results indicate that this approach can achieve good results.
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