https://111qqz.com/en/tags/%E5%B1%80%E9%83%A8%E6%95%8F%E6%84%9Fhash/Recent content in 局部敏感hash on 111qqz's blogHugo -- gohugo.ioen© 2015-2026 111qqzSat, 11 Mar 2017 07:59:00 +0000https://111qqz.com/en/post/acm-icpc/2017/2017-03-11-e5b180e983a8e6958fe6849fe59388e5b88ce7ae97e6b395locality-sensitive-hashinge5889de68ea2/Sat, 11 Mar 2017 07:59:00 +0000https://111qqz.com/en/post/acm-icpc/2017/2017-03-11-e5b180e983a8e6958fe6849fe59388e5b88ce7ae97e6b395locality-sensitive-hashinge5889de68ea2/<h3 class="relative group">前言： <div id="前言" class="anchor"></div> <span class="absolute top-0 w-6 transition-opacity opacity-0 -start-6 not-prose group-hover:opacity-100 select-none"> <a class="text-primary-300 dark:text-neutral-700 !no-underline" href="#%e5%89%8d%e8%a8%80" aria-label="Anchor">#</a> </span> </h3> <p>其实有了前文simhash算法的基础，局部敏感hash算法已经不存在理解上的问题了吧。。。毕竟simhash算法应该是局部敏感哈希算法的一种。。所以我就直接转载几篇我认为比较好的文档结合一下好了。。。会把比较重要的概念或者定义标记重点。</p>https://111qqz.com/en/post/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/%E6%8E%A8%E8%8D%90%E7%B3%BB%E7%BB%9F/2017-03-10-simhash-notes/Fri, 10 Mar 2017 03:33:08 +0000https://111qqz.com/en/post/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/%E6%8E%A8%E8%8D%90%E7%B3%BB%E7%BB%9F/2017-03-10-simhash-notes/<p>先放原始论文。。。以此表达对这个算法的敬意orz</p> <p><a href="http://www.australianscience.com.au/research/google/33026.pdf" target="_blank" rel="noreferrer">论文链接</a></p> <h2 class="relative group">问题引出： <div id="问题引出" class="anchor"></div> <span class="absolute top-0 w-6 transition-opacity opacity-0 -start-6 not-prose group-hover:opacity-100 select-none"> <a class="text-primary-300 dark:text-neutral-700 !no-underline" href="#%e9%97%ae%e9%a2%98%e5%bc%95%e5%87%ba" aria-label="Anchor">#</a> </span> </h2> <p>那天百度一面，frog学姐问了我如何判断两篇新闻稿的相似度的问题&hellip;.我满篇口胡&hellip;也只是回答了一些诸如从图片上考虑。。或者去掉stop word之后得到特征向量然后计算余弦值之类得到传统想法。。。</p>