Abstract
In standard human-to-human communication, people usually refer to existing facts and circumstances and build new useful, funny, or interesting information on the top of those. This common knowledge comprehends information usually found in news, articles, debates, lectures, etc. (factual knowledge), but also principles and definitions that can be found in collective intelligence projects such as Wikipedia (vocabulary knowledge). Attempts to build a common knowledge base are countless and comprehend both resources crafted by human experts or community efforts, such as WordNet and Freebase , a large collaborative knowledge base consisting of metadata composed mainly by its community members, and automatically-built knowledge bases, such as WikiTaxonomy , a taxonomy extracted from Wikipedia’s category links, YAGO, a semantic knowledge base derived from Wikipedia, WordNet, and GeoNames (http://geonames.org), and Never-Ending Language Learning (NELL), CMU’s semantic machine learning system.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
You can know the name of a bird in all the languages of the world, but when you’re finished, you’ll know absolutely nothing whatever about the bird. So let’s look at the bird and see what it’s doing – that’s what counts. I learned very early the difference between knowing the name of something and knowing something Richard Feynman .
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Cambria, E., Hussain, A. (2012). Tools. In: Sentic Computing. SpringerBriefs in Cognitive Computation, vol 2. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5070-8_4
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DOI: https://doi.org/10.1007/978-94-007-5070-8_4
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