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+          <a href="../top_k/" class="md-footer__link md-footer__link--prev" aria-label="上一页: 8.3. &amp;nbsp; Top-K 问题（New）" rel="prev">
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+        <title>8.3.   Top-K 问题（New） - Hello 算法</title>
      
    
    
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+        8.3. &nbsp; Top-K 问题（New）
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@ -2107,8 +2107,8 @@
 <h2 id="831">8.3.1. &nbsp; 方法一：遍历选择<a class="headerlink" href="#831" title="Permanent link">&para;</a></h2>
 <p>我们可以进行 <span class="arithmatex">\(k\)</span> 轮遍历，分别在每轮中提取第 <span class="arithmatex">\(1\)</span> , <span class="arithmatex">\(2\)</span> , <span class="arithmatex">\(\cdots\)</span> , <span class="arithmatex">\(k\)</span> 大的元素，时间复杂度为 <span class="arithmatex">\(O(nk)\)</span> 。</p>
 <p>该方法只适用于 <span class="arithmatex">\(k \ll n\)</span> 的情况，因为当 <span class="arithmatex">\(k\)</span> 与 <span class="arithmatex">\(n\)</span> 比较接近时，其时间复杂度趋向于 <span class="arithmatex">\(O(n^2)\)</span> ，非常耗时。</p>
-<p><img alt="遍历寻找最大的 \(k\) 个元素" src="../top_k.assets/top_k_traversal.png" /></p>
-<p align="center"> Fig. 遍历寻找最大的 $k$ 个元素 </p>
+<p><img alt="遍历寻找最大的 k 个元素" src="../top_k.assets/top_k_traversal.png" /></p>
+<p align="center"> Fig. 遍历寻找最大的 k 个元素 </p>

 <div class="admonition tip">
 <p class="admonition-title">Tip</p>
@ -2117,8 +2117,8 @@
 <h2 id="832">8.3.2. &nbsp; 方法二：排序<a class="headerlink" href="#832" title="Permanent link">&para;</a></h2>
 <p>我们可以对数组 <code>nums</code> 进行排序，并返回最右边的 <span class="arithmatex">\(k\)</span> 个元素，时间复杂度为 <span class="arithmatex">\(O(n \log n)\)</span> 。</p>
 <p>显然，该方法“超额”完成任务了，因为我们只需要找出最大的 <span class="arithmatex">\(k\)</span> 个元素即可，而不需要排序其他元素。</p>
-<p><img alt="排序寻找最大的 \(k\) 个元素" src="../top_k.assets/top_k_sorting.png" /></p>
-<p align="center"> Fig. 排序寻找最大的 $k$ 个元素 </p>
+<p><img alt="排序寻找最大的 k 个元素" src="../top_k.assets/top_k_sorting.png" /></p>
+<p align="center"> Fig. 排序寻找最大的 k 个元素 </p>

 <h2 id="833">8.3.3. &nbsp; 方法三：堆<a class="headerlink" href="#833" title="Permanent link">&para;</a></h2>
 <p>我们可以基于堆更加高效地解决 Top-K 问题，流程如下：</p>
@ -2131,7 +2131,7 @@
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 <div class="tabbed-block">
-<p><img alt="基于堆寻找最大的 \(k\) 个元素" src="../top_k.assets/top_k_heap_step1.png" /></p>
+<p><img alt="基于堆寻找最大的 k 个元素" src="../top_k.assets/top_k_heap_step1.png" /></p>
 </div>
 <div class="tabbed-block">
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