Query-related data extraction of hidden web documents

Abstract

The larger amount of information on the Web is stored in document databases and is not indexed by general-purpose search engines (i.e., Google and Yahoo). Such information is dynamically generated through querying databases β€” which are referred to as Hidden Web databases. Documents returned in response to a user query are typically presented using templategenerated Web pages. This paper proposes a novel approach that identifies Web page templates by analysing the textual contents and the adjacent tag structures of a document in order to extract query-related data. Preliminary results demonstrate that our approach effectively detects templates and retrieves data with high recall and precision

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    This paper was published in White Rose Research Online.

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