unstructured

简明释义

英[ʌnˈstrʌktʃəd]美[ʌnˈstrʌktʃərd]

adj. 结构凌乱的，无条理的，没有正式组织的；（服装）不用或少用内衬的

英英释义

单词用法

同义词

反义词

例句

1.The management of unstructured information is often categorized as content management.

对于非结构化信息的管理一般被分类为内容管理。

2.Typical errors occur when such unstructured cycles are added to the process model.

在向流程模型中添加此类非结构化循环时，将出现典型错误。

3.Regular databases can store both highly structured data and unstructured documents.

常规数据库可以存储高度结构化的数据和非结构化数据。

4.Information can be both structured and unstructured data.

信息可以为结构化和非结构化数据。

5.By default, nodes in Jackrabbit are set to nt: unstructured.

默认情况下，Jackrabbit的节点被设置为nt： unstructured。

6.Much of the movement has focused on the educational value of play, and efforts to restore recess and unstructured playtime to early childhood.

这场运动的重点是玩耍的教育价值，以及努力重建童年时期的休息和自由玩耍时间。

7.Now such programs can also interpret "unstructured" data, mainly free-form text.

现在，这类程序也能够解读“无结构的”数据，主要是自由格式文本。

8.In an unstructured (非结构化) environment, employees have the freedom to create their own workflows.

在一个非结构化的环境中，员工可以自由地创建自己的工作流程。

9.An unstructured (非结构化) interview allows for a more natural conversation between the interviewer and the candidate.

一次非结构化的面试允许面试官和候选人之间进行更自然的对话。

10.Many machine learning models struggle with unstructured (非结构化) data such as images and text.

许多机器学习模型在处理非结构化数据（如图像和文本）时会遇到困难。

11.The research team focused on analyzing unstructured (非结构化) data from customer feedback.

研究小组专注于分析来自客户反馈的非结构化数据。

12.The data collected from social media is often unstructured (非结构化), making it challenging to analyze.

从社交媒体收集的数据通常是非结构化的，这使得分析变得具有挑战性。

作文

In today's fast-paced world, the way we process information is constantly evolving. One term that has gained significant attention in recent years is unstructured data. This refers to information that does not have a predefined format or organization. Unlike structured data, which can be easily categorized and analyzed using traditional databases, unstructured data presents unique challenges and opportunities for individuals and organizations alike.To better understand the concept of unstructured data, we can look at various examples from our daily lives. Consider social media platforms, where users share thoughts, images, and videos without any specific guidelines on how to present this information. The posts, comments, and interactions on these platforms are all forms of unstructured data. They lack a consistent structure, making it difficult for algorithms and data analysts to interpret them effectively.Another example of unstructured data can be found in emails. Each email may contain text, attachments, links, and images, but there is no standard format that dictates how this information should be organized. As a result, extracting meaningful insights from emails requires advanced techniques such as natural language processing and machine learning.The rise of big data has made it increasingly important for organizations to find ways to manage and analyze unstructured data. Companies are now investing in technologies that can help them harness the power of this type of information. For instance, businesses can use sentiment analysis tools to gauge customer opinions based on reviews, tweets, and blog posts. These tools can process vast amounts of unstructured data, providing valuable insights that can inform marketing strategies and product development.However, managing unstructured data is not without its challenges. The sheer volume of information generated every day can be overwhelming, and traditional data management systems often struggle to keep up. Additionally, the lack of structure means that finding relevant information can be time-consuming and inefficient. Organizations must invest in training their employees to work with unstructured data effectively, ensuring they have the skills necessary to leverage this valuable resource.Moreover, privacy and security concerns arise when dealing with unstructured data. Since this type of data often contains personal information, organizations must take care to protect it from breaches and unauthorized access. Implementing robust security measures and adhering to data protection regulations is crucial in maintaining customer trust and safeguarding sensitive information.In conclusion, the concept of unstructured data is becoming increasingly relevant in our data-driven society. Understanding how to manage and analyze this type of information can provide individuals and organizations with a competitive edge. While there are challenges associated with unstructured data, the opportunities it presents are too significant to ignore. By embracing new technologies and methodologies, we can unlock the potential of unstructured data and use it to drive innovation and growth in various fields. As we continue to navigate the complexities of the digital age, mastering the art of working with unstructured data will be essential for success.

在当今快节奏的世界中，我们处理信息的方式正在不断演变。近年来，获得显著关注的一个术语是非结构化数据。这是指没有预定义格式或组织的信息。与可以通过传统数据库轻松分类和分析的结构化数据不同，非结构化数据为个人和组织带来了独特的挑战和机遇。为了更好地理解非结构化数据的概念，我们可以从日常生活中的各种例子入手。考虑社交媒体平台，用户在这些平台上分享思想、图像和视频，而没有任何具体的指导方针来呈现这些信息。这些平台上的帖子、评论和互动都是非结构化数据的形式。它们缺乏一致的结构，使得算法和数据分析师难以有效地解读它们。另一个非结构化数据的例子可以在电子邮件中找到。每封电子邮件可能包含文本、附件、链接和图像，但没有标准格式来规定这些信息的组织方式。因此，从电子邮件中提取有意义的见解需要先进的技术，如自然语言处理和机器学习。大数据的兴起使得组织越来越重要的是找到管理和分析非结构化数据的方法。公司现在正在投资于可以帮助他们利用这种类型信息的技术。例如，企业可以使用情感分析工具，根据评论、推文和博客文章来评估客户意见。这些工具可以处理大量的非结构化数据，提供有价值的见解，从而为市场营销策略和产品开发提供信息。然而，管理非结构化数据并非没有挑战。每天生成的信息量庞大，传统的数据管理系统往往难以跟上。此外，缺乏结构意味着查找相关信息可能耗时且低效。组织必须投资于培训员工，以有效地处理非结构化数据，确保他们具备利用这一宝贵资源所需的技能。此外，处理非结构化数据时会出现隐私和安全问题。由于这种类型的数据通常包含个人信息，组织必须小心保护其免受泄露和未经授权访问的影响。实施强有力的安全措施并遵守数据保护法规对于维护客户信任和保护敏感信息至关重要。总之，非结构化数据的概念在我们数据驱动的社会中变得越来越相关。了解如何管理和分析这种类型的信息可以为个人和组织提供竞争优势。尽管与非结构化数据相关的挑战存在，但它所带来的机会不容忽视。通过采用新技术和方法，我们可以释放非结构化数据的潜力，并利用它推动各个领域的创新和增长。在继续应对数字时代复杂性的过程中，掌握处理非结构化数据的艺术将对成功至关重要。