adjacency

adjacency 的音标是 [əˈdʒæsɪəns]，基本翻译是“接近，邻近；毗邻”。速记技巧是：ad（注意）＋jac（挤）＋ence（名词后缀）→adjacency。

adjacency 的英文词源为 adjacere（接近）+ ency（状态）。adjacency 表示“接近”的状态，通常指两个物体之间的空间关系。

adjacency 的变化形式主要有两种：其一是比较级 more adjacency，其二是最高级 most adjacency，表示“更为接近”或“最为接近”的状态。

相关单词与adjacency 相关的单词有 adjacently、adjoin、adhesion、adherence、adhesive 等。adjacently 意为“接近地”，表示在空间或时间上的接近。adjoin 意为“毗邻”，表示两个物体在空间上相邻。adhesion 意为“粘附”，与 adhesive（粘合剂）和adhesive（胶水）等词有关，表示物体之间的粘附关系。这些单词都与 adjacency 有着密切的联系，描述了物体之间的空间关系和物理特性。

举例来说，在建筑领域，adjacency 常常被用来描述房屋之间的距离和布局，比如一栋房子毗邻另一栋房子，或者两栋房子之间有足够的空间可以互相接近。在医学领域，adhesion 常常被用来描述手术后的伤口粘连，这可能会影响患者的康复。在艺术领域，adhesive 则常常被用来描述胶水等粘合剂，这些粘合剂在艺术创作中发挥着重要的作用。

总之，adjacency 作为英文单词，表示物体之间的空间关系和物理特性，具有广泛的应用领域和意义。

adjacency短语：

1. adjacency list - 邻接列表

2. adjacency matrix - 邻接矩阵

3. adjacency list of graph - 图邻接列表

4. adjacency matrix of graph - 图邻接矩阵

5. adjacency relation - 邻接关系

6. adjacency set - 邻接集

7. adjacency property - 邻接性质

双语例句：

1. The adjacency list is a convenient way to represent a graph. (邻接列表是表示图的一个方便的方法。)

2. The adjacency matrix can be used to quickly calculate the shortest path between two nodes. (邻接矩阵可以用来快速计算两个节点之间的最短路径。)

3. The adjacency relation between two people is determined by their social interactions. (两个人之间的邻接关系是由他们的社会互动决定的。)

4. In this graph, the adjacency set includes all the possible connections between nodes. (在这个图中，邻接集包括所有节点之间的可能连接。)

5. The adjacency property of a node determines its connectivity in the network. (节点的邻接性质决定了它在网络中的连通性。)

英文小作文：

Adjacency Matters

Adjacency is a fundamental concept in many fields, including graph theory and social networks. In a graph, adjacency refers to the relationship between two nodes, where they are connected by an edge. This concept is crucial in understanding the structure and properties of networks.

In social networks, for example, adjacency refers to the relationships between individuals, such as friendships, relationships, or connections. Understanding the adjacency matrix of a social network allows us to analyze its topology and identify key players and influential nodes. Similarly, in graph theory, adjacency matrices are used to represent complex networks and analyze their properties, such as shortest paths and community structure.

Adjacency also plays a key role in machine learning and data science, where it is used to represent relationships between data points. In recommender systems, for instance, the adjacency matrix represents the relationships between users and items, allowing us to identify patterns and predict user behavior. Similarly, in social media analysis, adjacency lists are used to represent user interactions and identify trends and patterns in online conversations.

Adjacency is a fundamental concept that underlies many real-world applications and has profound implications for understanding complex systems and networks.