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<h1 id="94">9.4. &nbsp; 小结<a class="headerlink" href="#94" title="Permanent link">&para;</a></h1>
<ul>
<li>图由顶点和边组成,可以表示为一组顶点和一组边构成的集合。</li>
<li>相比线性关系(链表)和分治关系(树),网络关系(图)的自由度更高,也从而更为复杂。</li>
<li>有向图的边存在方向,连通图中的任意顶点都可达,有权图的每条边都包含权重变量。</li>
<li>邻接矩阵使用方阵来表示图,每一行(列)代表一个顶点,矩阵元素代表边,使用 <span class="arithmatex">\(1\)</span><span class="arithmatex">\(0\)</span> 来表示两个顶点之间有边或无边。邻接矩阵的增删查操作效率很高,但占用空间大。</li>
<li>邻接表使用多个链表来表示图,第 <span class="arithmatex">\(i\)</span> 条链表对应顶点 <span class="arithmatex">\(i\)</span> ,其中存储了该顶点的所有邻接顶点。邻接表相对邻接矩阵更加节省空间,但由于需要通过遍历链表来查找边,因此时间效率较低。</li>
<li>当邻接表中的链表过长时,可以将其转化为红黑树或哈希表,从而提升查询效率。</li>
<li>从算法思想角度分析,邻接矩阵体现“以空间换时间”,邻接表体现“以时间换空间”</li>
<li>图可以用于建模各类现实系统,例如社交网络、地铁线路等。</li>
<li>树是图的一种特例,树的遍历也是图的遍历的一种特例。</li>
<li>图的广度优先遍历是一种由近及远、层层扩张的搜索方式,常借助队列实现。</li>
<li>图的深度优先遍历是一种优先走到底、无路可走再回头的搜索方式,常基于递归来实现。</li>
</ul>
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