Terabytes of tobler: Evaluating the first law in a massive, domain-neutral representation of world knowledge
|Terabytes of tobler: Evaluating the first law in a massive, domain-neutral representation of world knowledge|
|Author(s)||Hecht B., Moxley E.|
|Published in||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Keyword(s)||First Law of Geography, Spatial Autocorrelation, Spatial Dependence, Tobler's Law, Wikipedia (Extra: First Law of Geography, Spatial Autocorrelation, Spatial Dependence, Tobler's Law, Wikipedia, Correlation detectors, Image registration, Information theory, Linguistics, Knowledge representation)|
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Terabytes of tobler: Evaluating the first law in a massive, domain-neutral representation of world knowledge is a 2009 conference paper written in English by Hecht B., Moxley E. and published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
The First Law of Geography states, "everything is related to everything else, but near things are more related than distant things." Despite the fact that it is to a large degree what makes "spatial special," the law has never been empirically evaluated on a large, domain-neutral representation of world knowledge. We address the gap in the literature about this critical idea by statistically examining the multitude of entities and relations between entities present across 22 different language editions of Wikipedia. We find that, at least according to the myriad authors of Wikipedia, the First Law is true to an overwhelming extent regardless of language-defined cultural domain.
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