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A Text Similarity Meta-Search Engine Based on Document Fingerprints and Search Results Records

The retrieval of similar documents from the Web using documents as input instead of key-term queries is not currently supported by traditional Web search engines. One approach for solving the problem consists of fingerprint the document’s content into a set of queries that are submitted to a list of Web search engines. Afterward, results are merged, their URLs are fetched and their content is compared with the given document using text comparison algorithms. However, the action of requesting results to multiple web servers could take a significant amount of time and effort. In this work, a similarity function between the given document and retrieved results is estimated. The function uses as variables features that come from information provided by search engine results records, like rankings, titles and snippets...

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