A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit <a rel="external noopener" href="https://arxiv.org/pdf/0901.4180v2.pdf">the original URL</a>. The file type is <code>application/pdf</code>.
<span class="release-stage" >pre-print</span>
Cilibrasi and Vitanyi have demonstrated that it is possible to extract the meaning of words from the world-wide web. To achieve this, they rely on the number of webpages that are found through a Google search containing a given word and they associate the page count to the probability that the word appears on a webpage. Thus, conditional probabilities allow them to correlate one word with another word's meaning. Furthermore, they have developed a similarity distance function that gauges how<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/0901.4180v2">arXiv:0901.4180v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jfeffqflrnhkzncg5tp4rdld3q">fatcat:jfeffqflrnhkzncg5tp4rdld3q</a> </span>
more »... ely related a pair of words is. We present a specific counterexample to the triangle inequality for this similarity distance function.
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