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Deep Web sources discovery is one of the critical steps toward the large-scale information integration. In this paper, we present Deep Web sources crawling based on ontology, an enhanced crawling methodology. This focused crawling method based on ontology of Deep Web sources avoids to download a large number of irrelevant pages. Evaluation showed that this new approach has promising results.
There are a lot of pages on internet that are generated dynamically by the back-end database and the traditional searching engines can’t reach these pages, which are called Deep Web. These sources are structured and provide structured query interfaces and results. Organizing structured Deep Web sources by their domain can let users browse these valuable resources and is one of the critical steps toward...
Deep Web has been an important resource on the Web due to its rich and high quality information, leading to emerging a new application area in data mining and integrates. There may be hundreds or thousands of data sources providing data of relevance to a particular domain on the Web, So a primary challenge to large-scale deep Web data integration is to determine in what order to user integrate candidate...
Deep Web database classify is a key operation in organizing Deep Web resources. We address the problem of identifying the domain of Web databases with simple query interface. The existing methods can not effectively classify this type of Web databases, to solve this problem, we propose an new framework that can automatically and accurately classify Web databases with simple query interface based on...
An increasing number of databases have become Web accessible through HTML form-based search interfaces, which is so-called deep Web. For full utilization of deep Web resources and improving Web intelligence, which is essential for many applications such as deep Web data collection and comparison shopping, they need to be extracted out and assigned meaningful labels. In this paper, we present a synchronous-annotation...
A lot of high quality and wealthy data are hidden in backend database and search engines can not index this page, which is called Deep Web. It is mostly accessible through query interfaces. SDWS, a semantic search engine for Deep Web is presented. We are studying and implementing semantic Web technology to the each process of Deep Web information integrated, and expertise in Deep Web discovering,...
Object matching is a crucial step to integration of Deep Web sources. Existing methods suppose that record extraction and attribute segmentation are of high accuracy. But because of limitation of extraction techniques, information gained through the above methods is often incomplete. If we match object base on noisy and incomplete information, we can not achieve satisfactory performance. This paper...
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