mappings
简明释义
[数]映射
绘图，制图
[计]基因图的绘制（mapping 的复数）
英英释义
单词用法
测绘科学与技术，测绘学 | |
纹理映射；纹理贴图；材质贴图；贴图坐标 |
同义词
反义词
| 断开 | 网络中的断开导致了重大问题。 | ||
| 分歧 | There are several divergences in opinions among the team members. | 团队成员之间存在几个意见分歧。 |
例句
1.Complete transformations for mappings of data source models.
完成数据源模型之间的映射转换。
2.Document the current virtual device mappings on each VIOS.
记录每个VIOS上当前的虚拟设备映射。
3.Combining mappings can lead to good results.
组合映射可以得到好的结果。
4.Write type mappings for the client and server pieces.
为客户机和服务器段编写类型映射。
5.Compare these mappings in Table 1.
表1对这些映射进行了比较。
6.Further keyboard mappings for other character sets can be added.
还可以增加针对其他字符集的键盘映射。
7.The recommended mappings are set by default.
推荐使用默认的映射。
8.Review the mappings, and if satisfied click OK.
查看映射，如果满意的话就单击ok。
9.Picture: Dialog for managing category mappings.
图：类别映射对话框。
10.Our team is working on the mappings of user preferences to improve the recommendation system.
我们的团队正在进行用户偏好的映射，以改善推荐系统。
11.The software provides various data mappings to help users visualize their information.
该软件提供了多种数据映射，以帮助用户可视化他们的信息。
12.The database uses mappings to connect different tables and organize the data efficiently.
数据库使用映射将不同的表连接起来，以有效组织数据。
13.The project involves creating mappings between the old and new systems to ensure a smooth transition.
该项目涉及创建旧系统与新系统之间的映射，以确保平稳过渡。
14.In machine learning, feature mappings are crucial for transforming raw data into usable formats.
在机器学习中，特征映射对于将原始数据转换为可用格式至关重要。
作文
In the realm of data science and information technology, the concept of mappings plays a crucial role in understanding how different elements relate to one another. Essentially, mappings refer to the process of establishing a relationship or correspondence between two sets of data. This can be visualized as a bridge connecting two distinct points, allowing for the transfer and transformation of information. For instance, in programming, when we define a function that takes an input and produces an output, we are creating a specific mapping between the input values and their corresponding outputs. The significance of mappings extends beyond mere data representation; it is foundational in various fields such as mathematics, computer science, and even linguistics. In mathematics, mappings are often illustrated through functions, where each input from a domain is assigned to exactly one output in a range. This concept helps mathematicians solve complex problems by simplifying relationships into more manageable forms. In the context of databases, mappings are essential for defining how data is structured and accessed. Database administrators utilize mappings to create schemas that dictate how data entities relate to one another. For example, in a relational database, a user table may have a mapping to an orders table, indicating which users have placed which orders. This relational mapping enables efficient data retrieval and manipulation, showcasing the practical application of this concept in everyday technology. Moreover, mappings are vital in the field of machine learning. Algorithms often rely on mappings to learn from data and make predictions. During the training phase, a model identifies patterns and creates a mapping between input features and target outcomes. This learned mapping is then used to predict future results based on new input data. The effectiveness of a machine learning model largely depends on how well it captures these mappings. On a broader scale, mappings can also refer to cognitive processes in human understanding. When we learn new concepts, our brains create mental mappings that connect new information with existing knowledge. This cognitive mapping allows us to navigate complex ideas and form a cohesive understanding of various subjects. For instance, when studying geography, we might create a mental mapping of countries and their capitals, facilitating better retention and recall of information. In conclusion, the term mappings encompasses a wide array of applications across different disciplines. From data representation in programming and databases to cognitive processes in learning, mappings serve as a fundamental tool for establishing connections and understanding relationships. As technology continues to evolve, the importance of mappings will only grow, highlighting the need for individuals in various fields to grasp this essential concept. Understanding mappings not only enhances our technical skills but also enriches our cognitive abilities, making it a vital area of study for anyone looking to thrive in an increasingly interconnected world.
在数据科学和信息技术领域，mappings的概念在理解不同元素之间的关系中起着至关重要的作用。基本上，mappings指的是建立两个数据集之间关系或对应的过程。这可以被视为连接两个不同点的桥梁，允许信息的传递和转换。例如，在编程中，当我们定义一个接受输入并产生输出的函数时，我们就在创建一个特定的mapping，将输入值与其对应的输出相联系。mappings的重要性超越了简单的数据表示；它是数学、计算机科学甚至语言学等多个领域的基础。在数学中，mappings通常通过函数来说明，其中域中的每个输入都被分配到范围中的一个输出。这个概念帮助数学家通过将关系简化为更易于管理的形式来解决复杂的问题。在数据库的上下文中，mappings对于定义数据的结构和访问至关重要。数据库管理员利用mappings创建模式，这些模式决定了数据实体之间的关系。例如，在一个关系数据库中，用户表可能与订单表存在mapping，指示哪些用户下了哪些订单。这种关系mapping使得高效的数据检索和操作成为可能，展示了这一概念在日常技术中的实际应用。此外，mappings在机器学习领域也至关重要。算法通常依赖于mappings从数据中学习并做出预测。在训练阶段，模型识别模式并创建输入特征与目标结果之间的mapping。然后，这种学习到的mapping用于根据新的输入数据进行未来结果的预测。机器学习模型的有效性在很大程度上取决于它捕获这些mappings的能力。在更广泛的范围内，mappings也可以指人类理解中的认知过程。当我们学习新概念时，大脑会创建心理mappings，将新信息与现有知识联系起来。这种认知mapping使我们能够导航复杂的想法，并形成对各种主题的连贯理解。例如，在学习地理时，我们可能会创建一个国家及其首都的心理mapping，从而促进信息的更好记忆和回忆。总之，mappings一词涵盖了不同学科的广泛应用。从编程和数据库中的数据表示到学习中的认知过程，mappings作为建立连接和理解关系的基本工具。随着技术的不断发展，mappings的重要性只会增加，这突显了各个领域的人们掌握这一基本概念的必要性。理解mappings不仅增强了我们的技术技能，还丰富了我们的认知能力，使其成为任何希望在日益互联的世界中蓬勃发展的人的重要研究领域。
