aggregation

简明释义

英[ˌæɡrɪˈɡeɪʃn]美[ˌæɡrɪˈɡeɪʃn]

n. 聚集，聚合；（互联网）相关内容项的集合；聚集体，集合体

复 数 a g g r e g a t i o n s

英英释义

单词用法

同义词

反义词

例句

1.But this distinction misses the point that it is processing and aggregation, not the mere possession of bits, that gives the data value.

但这种区别忽略了一点，即正是对信息的处理和收集，而不是仅仅拥有信息，让数据有了价值。

2.This is more commonly called server aggregation or grid computing.

这通常称为服务器聚合或网格计算。

3.Three words: search, aggregation, conversation.

答案仍然是：搜索、聚合和会话。

4.Service aggregation can be implemented using collaboration logic.

可以通过使用协作逻辑实现服务聚合。

5.Without it, FOAF aggregation just doesn't work.

没有它，FOAF聚集就不能工作。

6.You could manage this aggregation by placing the messages in a message group.

可以通过将消息放入到消息组中对此聚合进行管理。

7.Etherchannel is a port link aggregation technology.

以太信道是一种端口链路聚合技术。

8.Thrombomodulin can entirely inhibit thrombin and ristocetin-induced platelet aggregation.

血栓调节蛋白可完全抑制凝血酶和利斯托司汀诱导的血小板聚集。

9.The aggregation of resources can lead to more efficient project management.

资源的聚合可以导致更有效的项目管理。

10.An aggregation of opinions was collected during the community meeting.

在社区会议上收集了意见的聚合。

11.In statistics, aggregation is used to summarize large datasets into more manageable forms.

在统计学中，聚合用于将大型数据集汇总成更易于管理的形式。

12.The software uses aggregation techniques to combine multiple reports into one.

该软件使用聚合技术将多个报告合并为一个。

13.The aggregation of data from various sources helps in making informed decisions.

来自不同来源的数据聚合有助于做出明智的决策。

作文

In today's data-driven world, the concept of aggregation is becoming increasingly important. Aggregation refers to the process of collecting and combining multiple pieces of information into a single, comprehensive dataset. This practice is essential in various fields, including business, healthcare, and social sciences, as it allows for better analysis and decision-making based on a larger pool of data.For instance, in the business sector, companies often gather customer feedback from various sources such as surveys, social media, and sales data. By using aggregation techniques, they can compile this information to identify trends in customer preferences and behaviors. This aggregated data enables businesses to tailor their products and marketing strategies to meet the needs of their target audience more effectively.Similarly, in healthcare, aggregation plays a crucial role in improving patient outcomes. Health organizations collect data from numerous patients, including medical histories, treatment responses, and demographic information. Through aggregation, healthcare professionals can analyze this vast amount of data to discover patterns that inform treatment protocols and public health initiatives. For example, understanding how different demographics respond to specific treatments can lead to more personalized and effective healthcare solutions.Moreover, in social sciences, researchers often rely on aggregation to draw meaningful conclusions from their studies. By compiling data from various surveys and studies, they can create a more accurate representation of societal trends and issues. This aggregated information can help policymakers make informed decisions that address the needs of the population, such as implementing new laws or funding programs that benefit the community.However, while aggregation offers numerous advantages, it also presents challenges. One primary concern is the potential loss of individual data granularity. When data is aggregated, some unique characteristics may be overlooked, leading to generalized conclusions that do not apply to every individual. Therefore, it is essential for researchers and analysts to strike a balance between utilizing aggregation for broader insights and maintaining the integrity of individual data points.Additionally, ethical considerations arise when aggregating data, particularly concerning privacy. Organizations must ensure that they are compliant with data protection regulations and that they handle personal information responsibly. Anonymizing data during the aggregation process can help mitigate privacy risks while still allowing for valuable insights.In conclusion, aggregation is a vital process that enhances our ability to analyze and interpret data across various domains. By combining information from multiple sources, we can uncover patterns and trends that inform decision-making and improve outcomes. However, it is crucial to approach aggregation thoughtfully, considering both its benefits and the potential drawbacks. As we continue to navigate an increasingly complex data landscape, mastering the art of aggregation will undoubtedly be a key skill for future success.

在当今数据驱动的世界中，聚合这一概念变得越来越重要。聚合是指将多个信息片段收集并组合成一个综合数据集的过程。这一做法在商业、医疗保健和社会科学等多个领域至关重要，因为它允许基于更大数据池进行更好的分析和决策。例如，在商业领域，公司通常会从各种来源收集客户反馈，如调查、社交媒体和销售数据。通过使用聚合技术，他们可以汇总这些信息，以识别客户偏好和行为的趋势。这些汇总的数据使企业能够更有效地调整其产品和营销策略，以满足目标受众的需求。同样，在医疗保健中，聚合在改善患者结果方面发挥着关键作用。健康组织收集来自众多患者的数据，包括病史、治疗反应和人口统计信息。通过聚合，医疗专业人员可以分析这大量数据，以发现模式，从而为治疗协议和公共卫生倡议提供信息。例如，了解不同人口统计群体对特定治疗的反应可以导致更个性化和有效的医疗解决方案。此外，在社会科学中，研究人员通常依赖于聚合来从他们的研究中得出有意义的结论。通过汇总来自各种调查和研究的数据，他们可以创建更准确的社会趋势和问题的表现。这些汇总的信息可以帮助政策制定者做出明智的决策，解决人口的需求，例如实施新法律或资助有利于社区的项目。然而，虽然聚合提供了许多优势，但也带来了挑战。一个主要的担忧是可能会失去个体数据的细节。当数据被聚合时，一些独特的特征可能会被忽视，从而导致普遍化的结论不适用于每个个体。因此，研究人员和分析师必须在利用聚合以获取更广泛的见解与保持个体数据点的完整性之间取得平衡。此外，在聚合数据时，伦理考虑也会出现，尤其是在隐私方面。组织必须确保遵守数据保护法规，并负责任地处理个人信息。在聚合过程中对数据进行匿名化可以帮助减少隐私风险，同时仍然允许获得有价值的见解。总之，聚合是一个至关重要的过程，它增强了我们在各个领域分析和解释数据的能力。通过结合来自多个来源的信息，我们可以发现模式和趋势，从而为决策提供信息并改善结果。然而，重要的是要以深思熟虑的方式接近聚合，考虑其好处和潜在缺点。随着我们继续在日益复杂的数据环境中航行，掌握聚合的艺术无疑将成为未来成功的关键技能。