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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Subsets and Supermajorities: Optimal Hashing-based Set Similarity Search · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1904.04045/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1904.04045/feed.xml" rel="self" type="application/rss+xml" /><item><title>Subsets and Supermajorities: Optimal Hashing-based Set Similarity Search — mentioned by thomasahle</title><link>https://news.ycombinator.com/item?id=23476766</link><guid isPermaLink="false">urn:hackerpapers:mention:1904.04045:23476766</guid><pubDate>Wed, 10 Jun 2020 13:28:47 GMT</pubDate><description>&lt;p&gt;I love this quote from a follow up paper: &amp;gt; Interestingly, hash algorithms with collision probabilities equal to JP have already been unintentionally presented before JP was actually discovered and thoroughly analyzed in [8]. In [7] a data structure called HistoSketch was proposed to calculate signatures for JN ... after some simplifications and thanks to a nonequivalent transformation that eliminated the scale dependence, the final HistoSketch algorithm had a collision probability equal to JP instead of the originally desired JN. It&amp;#x27;s none the less a very interesting measure. Thanks for…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1904.04045/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.DS</category></item></channel></rss>
