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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Finding Structure in Text, Genome and Other Symbolic Sequences · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1207.1847/</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/1207.1847/feed.xml" rel="self" type="application/rss+xml" /><item><title>Finding Structure in Text, Genome and Other Symbolic Sequences — mentioned by ted_dunning</title><link>https://news.ycombinator.com/item?id=43968999</link><guid isPermaLink="false">urn:hackerpapers:mention:1207.1847:43968999</guid><pubDate>Tue, 13 May 2025 01:39:52 GMT</pubDate><description>&lt;p&gt;Regarding item (2), Salton did talk about this and many systems from the early TREC times implemented them. In my own work, I found that relevance feedback worked very well with only a few dozen judgements. See Chapter 7 starting on page 83 in my dissertation: https://arxiv.org/abs/1207.1847 Note also that the evaluation of Luduan in that chapter compared against state-of-the-art (for the time) back-of-words systems but also an early word embedding retrieval system (Convectis from HNC).&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1207.1847/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
