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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Semantic Folding Theory And its Application in Semantic Fingerprinting · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1511.08855/</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/1511.08855/feed.xml" rel="self" type="application/rss+xml" /><item><title>Semantic Folding Theory And its Application in Semantic Fingerprinting — mentioned by 19h</title><link>https://news.ycombinator.com/item?id=36688784</link><guid isPermaLink="false">urn:hackerpapers:mention:1511.08855:36688784</guid><pubDate>Wed, 12 Jul 2023 00:02:28 GMT</pubDate><description>&lt;p&gt;Unfortunately, I can&amp;#x27;t. We have some projects bubbling around that may see the light of the day eventually but given the myriads of NDAs that stack on top of each other this is rather unlikely. That said, here&amp;#x27;s some reading material on the underlying ideas: - https://en.wikipedia.org/wiki/Semantic_folding - https://arxiv.org/pdf/1511.08855.pdf (&amp;quot;Semantic Folding Theory And its Application in Semantic Fingerprinting&amp;quot;) This is _not_ TF-IDF. Once you have built the &amp;quot;relation fingerprints&amp;quot; of each word, the fingerprint lookup complexity is o(1) as you&amp;#x27;ll essentially only load a massive LUT of…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1511.08855/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Semantic Folding Theory And its Application in Semantic Fingerprinting — mentioned by 19h</title><link>https://news.ycombinator.com/item?id=33461761</link><guid isPermaLink="false">urn:hackerpapers:mention:1511.08855:33461761</guid><pubDate>Fri, 04 Nov 2022 03:30:52 GMT</pubDate><description>&lt;p&gt;We&amp;#x27;ve been doing significant research using HTM[1][2][3][4] w/ SDR[5] similar to the proprietary implementation of Semantic Folding[6] and were able to classify literally gigabytes of documents per second on FPGAs. HTM aims to resemble the architecture of the Neocortex. I simply don&amp;#x27;t understand why literally everyone immediately jumps at CNNs, RNNs (transformers et al.) -- they&amp;#x27;re extremely expensive, slow and definitely not usable for SIGINT-sized intel projects. [1] https://arxiv.org/pdf/2112.14820.pdf [2] https://arxiv.org/pdf/1402.2902.pdf [3] https://arxiv.org/pdf/1509.08255.pdf [4]…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1511.08855/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
