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Assessing relevance and trust of the deep web

Sources and results based on inter-source agreement

Deep web search engines face the formidable challenge of retrieving high-quality results from the vast collection of searchable databases. Deep web search is a two-step process of selecting high-quality sources and ranking the results from the selected sources. Though there are existing methods for both the steps, they assess the relevance of the sources and the results using the query-result similarity. When applied to the deep web these methods have two deficiencies. The first is that they are agnostic to the correctness (trustworthiness) of the results. Secondly, the query-based relevance does not consider the importance of the results and sources...

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