graph theory 的音標(biāo)是[?gr?f ?θ??ri]，基本翻譯是圖論，速記技巧可以是：gr=圖形+phi=關(guān)系+ty=理論。

Graph theory（圖論）這個詞源于希臘語，意為“圖形理論”。它的主要研究對象是圖形，包括節(jié)點和邊。這個詞的變化形式包括復(fù)數(shù)形式的“graphs”，過去式和過去分詞形式的“graphied”或“graphied/graphied”，以及現(xiàn)在分詞形式的“graphing”。相關(guān)單詞包括：

1. Network（網(wǎng)絡(luò)）：與圖論密切相關(guān)，網(wǎng)絡(luò)是指由節(jié)點和邊組成的復(fù)雜圖形，通常用于描述現(xiàn)實世界中的系統(tǒng)，如社交網(wǎng)絡(luò)、交通網(wǎng)絡(luò)等。

2. Node（節(jié)點）：在圖論中，節(jié)點是圖形的頂點，是圖形中的基本元素之一。

3. Edge（邊）：邊是連接兩個節(jié)點的線段，是圖形的邊或分支。

4. Graph（圖）：最簡單的圖形是由節(jié)點和邊組成的集合，稱為圖。

5. Diagram（圖表）：一種圖形表示方法，通常用于展示復(fù)雜系統(tǒng)或數(shù)據(jù)之間的關(guān)系，可以看作是一種廣義的圖論。

6. Topology（拓?fù)洌和負(fù)涫茄芯繄D形結(jié)構(gòu)性質(zhì)的理論，包括節(jié)點的排列、邊的方向等。

7. Vertex（頂點）：在圖論中，頂點與節(jié)點意義相近，但更常用于描述有向圖或網(wǎng)絡(luò)中的特定點。

8. Contraction（收縮）：一種圖論操作，用于減少圖的邊數(shù)或節(jié)點數(shù)。

9. Expansion（擴(kuò)張）：與收縮相反的操作，用于增加圖的邊數(shù)或節(jié)點數(shù)。

10. Embedding（嵌入）：將圖論中的圖形映射到實際空間中的過程。

常用短語：

1. graph theory analysis

2. graph theory concepts

3. graph theory algorithms

4. graph theory applications

5. graph theory concepts in practice

6. graph theory concepts in education

7. graph theory in social networks

例句：

1. The graph theory analysis of the network is crucial for its efficient operation.

2. The graph theory concepts are essential for understanding the structure of complex systems.

3. The graph theory algorithms can be used to efficiently solve optimization problems.

4. The graph theory applications are widespread in various fields of science and technology.

5. Practicing graph theory concepts in education helps students develop analytical skills.

6. Social networks can be effectively analyzed using graph theory concepts.

英文小作文：

Graph Theory and Social Networks

Social networks have become an integral part of our daily lives, and understanding their structure and dynamics is crucial for effective communication and information dissemination. Graph theory, a mathematical discipline that studies the properties of networks, provides a powerful tool for analyzing social networks. Using graph theory, one can identify key players, measure centrality, and investigate patterns of connectivity that underlie social networks.

Moreover, graph theory can be used to design algorithms for recommending content and optimizing user experiences in social networks. By analyzing the graph structure of social networks, one can identify patterns that indicate potential risks and threats, and develop strategies for mitigating them. Therefore, graph theory has a significant role to play in the future development of social networks, ensuring that they remain effective, efficient, and user-friendly.