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Creators/Authors contains: "Podkorytov, Maksim"

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  1. ; (, Conference: 2018 IEEE International Conference on Big Data (Big Data))
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  2. ; ; ; ; (, WWW '18 Companion Proceedings of the The Web Conference 2018)
    Variety of Big data is a significant impediment for anyone who wants to search inside a large-scale structured dataset. For example, there are millions of tables available on the Web, but the most relevant search result does not necessarily match the keyword-query exactly due to a variety of ways to represent the same information. Here we describe Hybrid.AI, a learning search engine for large-scale structured data that uses automatically generated machine learning classifiers and Unified Famous Objects (UFOs) to return the most relevant search results from a large-scale Web tables corpora. We evaluate it over this corpora, collecting 99 queries and their results from users, and observe significant relevance gain. 
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