https://terms-en.ai-term-hub.com/zh/tags/data-structures/Recent content in Data Structures on 中文AI术语词典Hugozh-cnSat, 18 Jul 2026 11:44:45 +0000https://terms-en.ai-term-hub.com/zh/terms/tensor/Sat, 18 Jul 2026 11:35:54 +0000https://terms-en.ai-term-hub.com/zh/terms/tensor/<h2 id="definition">Definition</h2> <p>在计算机科学和深度学习中，张量是一种数学对象，它将标量、向量和矩阵推广到更高维度。它由其秩（维度数量）和形状等特征定义。</p> <h3 id="summary">Summary</h3> <p>一种多维数组，是深度学习框架中的基本数据结构。</p> <h2 id="key-concepts">Key Concepts</h2> <ul> <li>秩</li> <li>形状</li> <li>维度</li> <li>广播机制</li> </ul> <h2 id="use-cases">Use Cases</h2> <ul> <li>图像处理（4D张量）</li> <li>神经网络权重存储</li> <li>批量数据输入</li> </ul> <h2 id="code-example">Code Example</h2> <div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-python" data-lang="python"><span style="display:flex;"><span><span style="color:#f92672">import</span> torch </span></span><span style="display:flex;"><span>t <span style="color:#f92672">=</span> torch<span style="color:#f92672">.</span>tensor([[<span style="color:#ae81ff">1</span>, <span style="color:#ae81ff">2</span>], [<span style="color:#ae81ff">3</span>, <span style="color:#ae81ff">4</span>]]) </span></span></code></pre></div><h2 id="related-terms">Related Terms</h2> <ul> <li><a href="https://terms-en.ai-term-hub.com/en/terms/matrix-%E7%9F%A9%E9%98%B5/">Matrix (矩阵)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/vector-%E5%90%91%E9%87%8F/">Vector (向量)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/deep-learning-%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/">Deep Learning (深度学习)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/numpy-%E6%95%B0%E5%80%BC%E8%AE%A1%E7%AE%97%E5%BA%93/">NumPy (数值计算库)</a></li> </ul>https://terms-en.ai-term-hub.com/zh/terms/hierarchical_navigable_small_world/Sat, 18 Jul 2026 11:20:58 +0000https://terms-en.ai-term-hub.com/zh/terms/hierarchical_navigable_small_world/<h2 id="definition">Definition</h2> <p>分层可导航小世界（HNSW）算法构建了一个多层图结构，其中每一层包含下一层节点的子集。导航从顶层开始，逐步向下移动到更详细的层级，直到找到最近的邻居。这种方法结合了小世界网络的快速收敛特性和分层结构的效率，实现了高维向量的高效近似最近邻搜索。</p> <h3 id="summary">Summary</h3> <p>一种基于图的数据结构，用于在高维空间中实现高效的近似最近邻搜索。</p> <h2 id="key-concepts">Key Concepts</h2> <ul> <li>图搜索</li> <li>近似最近邻</li> <li>多层图</li> <li>对数复杂度</li> </ul> <h2 id="use-cases">Use Cases</h2> <ul> <li>向量搜索</li> <li>推荐引擎</li> <li>图像检索</li> </ul> <h2 id="related-terms">Related Terms</h2> <ul> <li><a href="https://terms-en.ai-term-hub.com/en/terms/k-nearest-neighbors-k%E8%BF%91%E9%82%BB/">K-Nearest Neighbors (K近邻)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/faiss-facebook-ai-similarity-search%E5%BA%93/">Faiss (Facebook AI Similarity Search库)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/annoy-spotify%E5%BC%80%E5%8F%91%E7%9A%84%E8%BF%91%E4%BC%BC%E6%9C%80%E8%BF%91%E9%82%BB%E5%BA%93/">Annoy (Spotify开发的近似最近邻库)</a></li> </ul>https://terms-en.ai-term-hub.com/zh/terms/bloom/Sat, 18 Jul 2026 11:09:30 +0000https://terms-en.ai-term-hub.com/zh/terms/bloom/<h2 id="definition">Definition</h2> <p>虽然历史上指本杰明·布鲁姆的教育分类法，但在现代人工智能语境中，它通常指由BigScience开发的Bloom文本嵌入模型。该模型生成高质量的……</p> <h3 id="summary">Summary</h3> <p>在机器学习中，“Bloom”通常指应用于人工智能教育的布鲁姆分类法，或特定的嵌入模型（如Bloom文本嵌入模型）。</p> <h2 id="key-concepts">Key Concepts</h2> <ul> <li>文本嵌入</li> <li>语义搜索</li> <li>布隆过滤器</li> <li>概率数据结构</li> </ul> <h2 id="use-cases">Use Cases</h2> <ul> <li>自然语言处理 (NLP)</li> <li>数据库索引优化</li> <li>内容推荐系统</li> </ul> <h2 id="related-terms">Related Terms</h2> <ul> <li><a href="https://terms-en.ai-term-hub.com/en/terms/embedding-%E5%B5%8C%E5%85%A5/">Embedding (嵌入)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/vector-database-%E5%90%91%E9%87%8F%E6%95%B0%E6%8D%AE%E5%BA%93/">Vector Database (向量数据库)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/hash-function-%E5%93%88%E5%B8%8C%E5%87%BD%E6%95%B0/">Hash Function (哈希函数)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/nlp-%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/">NLP (自然语言处理)</a></li> </ul>https://terms-en.ai-term-hub.com/zh/terms/ball_tree/Sat, 18 Jul 2026 11:08:27 +0000https://terms-en.ai-term-hub.com/zh/terms/ball_tree/<h2 id="definition">Definition</h2> <p>球树将数据点划分为嵌套的超球体（球），而不是超矩形。这种结构允许通过计算距离来进行高效的剪枝，从而加速最近邻查询。</p> <h3 id="summary">Summary</h3> <p>一种用于组织空间中点的二叉树数据结构，优化高维数据集中的最近邻搜索。</p> <h2 id="key-concepts">Key Concepts</h2> <ul> <li>超球体划分</li> <li>最近邻搜索</li> <li>高维数据</li> <li>树遍历</li> </ul> <h2 id="use-cases">Use Cases</h2> <ul> <li>K近邻算法 (KNN)</li> <li>聚类分析</li> <li>异常检测</li> </ul> <h2 id="code-example">Code Example</h2> <div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-python" data-lang="python"><span style="display:flex;"><span><span style="color:#f92672">from</span> sklearn.neighbors <span style="color:#f92672">import</span> BallTree </span></span><span style="display:flex;"><span><span style="color:#f92672">import</span> numpy <span style="color:#66d9ef">as</span> np </span></span><span style="display:flex;"><span>X <span style="color:#f92672">=</span> np<span style="color:#f92672">.</span>random<span style="color:#f92672">.</span>rand(<span style="color:#ae81ff">100</span>, <span style="color:#ae81ff">5</span>) </span></span><span style="display:flex;"><span>tree <span style="color:#f92672">=</span> BallTree(X, metric<span style="color:#f92672">=</span><span style="color:#e6db74">&#39;euclidean&#39;</span>) </span></span></code></pre></div><h2 id="related-terms">Related Terms</h2> <ul> <li><a href="https://terms-en.ai-term-hub.com/en/terms/kd-tree-k%E7%BB%B4%E6%A0%91/">KD-tree (K维树)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/k-nearest-neighbors-k%E8%BF%91%E9%82%BB/">K-Nearest Neighbors (K近邻)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/curse-of-dimensionality-%E7%BB%B4%E5%BA%A6%E7%81%BE%E9%9A%BE/">Curse of Dimensionality (维度灾难)</a></li> </ul>https://terms-en.ai-term-hub.com/zh/terms/graph/Sat, 18 Jul 2026 10:51:41 +0000https://terms-en.ai-term-hub.com/zh/terms/graph/<h2 id="definition">Definition</h2> <p>图是人工智能中的一种基本数据结构，由顶点（节点）和边（链接）组成，用于表示关系。图神经网络（GNN）利用这种结构在非欧几里得数据上进行学习。</p> <h3 id="summary">Summary</h3> <p>由通过边连接的节点组成的数学结构，用于表示实体之间的关系。</p> <h2 id="key-concepts">Key Concepts</h2> <ul> <li>节点/顶点</li> <li>边</li> <li>邻接矩阵</li> <li>拓扑</li> </ul> <h2 id="use-cases">Use Cases</h2> <ul> <li>知识图谱</li> <li>社交网络分析</li> <li>分子属性预测</li> </ul> <h2 id="related-terms">Related Terms</h2> <ul> <li><a href="https://terms-en.ai-term-hub.com/en/terms/gnn-%E5%9B%BE%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C/">GNN (图神经网络)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/network-%E7%BD%91%E7%BB%9C/">Network (网络)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/topology-%E6%8B%93%E6%89%91/">Topology (拓扑)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/edge-%E8%BE%B9/">Edge (边)</a></li> </ul>