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Knowledge Vault

The Knowledge Vault is a knowledge base created by Google. As of 2014, it contained 1.6 billion facts which had been collated automatically from the Internet.[1]

The difference between Google's existing Knowledge Graph and their Knowledge Vault is the way that facts are accumulated. The Knowledge Graph pulls in information from trusted[according to whom?] sources like Freebase and Wikipedia, both of which are crowdsourced initiatives. The Knowledge Vault is an accumulation of facts from across the entire web. It is a mix of both high-confidence results and low-confidence or ‘dirty’ ones and machine learning is used to rank them.


The concept behind the Knowledge Vault was presented in a paper authored by Xin Luna Dong, Evgeniy Gabrilovich, Geremy Heitz, Wilko Horn, Ni Lao, Kevin Murphy, Thomas Strohmann, Shaohua Sun and Wei Zhang - all of them from Google Research.[2]

The approach has been through various tests by Google in other search and web products. The official blog post announcing the Knowledge Graph and the transition from “Strings to Things”[3] says that the Knowledge Graph isn't just rooted in public sources such as Freebase, Wikipedia and the CIA World Factbook. It's also augmented at a much larger scale — because we're focused on comprehensive breadth and depth."[clarification needed]

One of the earliest examples was the Google Q&A service that used artificial intelligence and a large corpus of data to provide direct answers to questions. It is explained in a presentation by Google's Peter Norvig.[4] The Q&A service was discontinued in July 2014.


  1. ^ Hal Hodson (20 August 2014), "Google's fact-checking bots build vast knowledge bank", New Scientist 
  2. ^ Dong, X. L., Murphy, K., Gabrilovich, E., Heitz, G., Horn, W., Lao, N., ... & Zhang, W. (2014). Knowledge Vault: A Web-scale approach to probabilistic knowledge fusion.
  3. ^ "Introducing the Knowledge Graph: things, not strings". May 16, 2012. 
  4. ^ "Peter Norvig presentation on fact mining across the web".