Hybrid.AI: A Learning Search Engine for Large-scale Structured Data


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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Please refer to ACM.