数据挖掘（Data Mining）

NO.1：
In the current era of big data, the mining and analysis of massive data is particularly important. Data mining
technology has been widely applied in the fields of media, finance,
medical care, transportation and e-commerce.However, the complexity and
diversity of big data and the particularity of the application of data
mining technology in various industries have also put forward new
theoretical and technical challenges in the field of data mining.

NO.2：
The era of big data for the data mining
technology has brought more opportunities and problems, such as the big
data content for more efficient data mining algorithm and the
accumulation of large data more quickness requirement of real-time data
mining algorithms, the complexity of the large data diversity requires
more flexible data mining algorithm, the universality of big data in all
walks of life to the particularity in the field of data mining
algorithm, etc.This also presents a new demand for data mining.

翻译

NO1

在大数据时代，大量数据的挖掘和分析变得非常重要。

数据挖掘技术已经在媒体，金融，医疗，交通，电子商务领域得到了广泛应用。

然而，大数据的复杂性与多样性以及数据挖掘技术在许多领域的特殊应用也给大数据领域带来了新的理论与技术的挑战。

NO2

大数据时代为数据挖掘技术带来了更多的机遇和问题，比如大数据内容的处理需要更高效的数据挖掘算法，大数据的更快的堆积处理需要更实时的数据挖掘算法，庞大数据的多样性的复杂性需要更灵活的数据挖掘算法，大数据在各行各业的广泛性对应着大数据挖掘算法在各领域的独特性等等要求。

这也给数据挖掘领域带来了一些新要求。

人工智能（Artificial Intelligence）

NO.1：
From AlphaGo to unmanned driving, from speech recognition to face recognition, artificial intelligence
has become one of the most important technologies in the modern era.
Artificial intelligence technology has been widely used in scientific
discovery, economic construction, social life and other
fields.Artificial intelligence research and development has been
promoted to the national strategic level. With the continuous
development of information technologies such as big data, cloud computing and Internet of things, artificial intelligence research is facing new challenges in theory, method and application.

NO.2：
In recent years, the rapid development of
artificial intelligence technology makes its application expand rapidly.
However, the traditional computer architecture has many shortcomings in processing speed,
energy consumption and convenience of use for the application of
artificial intelligence.With the development of the application of
artificial intelligence, the architecture oriented to artificial
intelligence has become an important direction in the research and
development of architecture

NO1

从alphaGo 到无人驾驶，从语音识别到脸部识别，人工智能已经成为了现代最重要的技术之一。

人工智能已经广泛应用于科学探索，经济结构，社会生活和其他领域。

人工智能的研究与发展已经提升到了国家战略的水平。

随着大数据，云计算，物联网领域的信息技术的不断发展，人工智能的研究面临着在理论，方法以及应用方面的新挑战。

 NO2

最近几年，人工智能技术的快速发展使得它的应用迅速扩张。

然而，对于人工智能的应用，传统计算机体系结构在处理速度，能量损耗，使用方便存在着许多缺点，面向人工智能的架构已成为了架构研究与发展的重要方向。

深度学习（Deep Learning）

NO.1：
Deep learning has achieved a lot in search technology, data mining, machine learning, machine translation, natural language processing, multimedia learning,
voice, recommendation and personalization, and other related
fields.Deep learning enables machines to imitate human activities such
as audiovisual and thinking, solves many complex pattern recognition
problems, and makes great progress in related technologies of artificial
intelligence.

NO1

深度学习在搜索技术，数据挖掘，机器学习，机器翻译，自然语言处理，多媒体的学习，声音，个性化推荐和其他相关领域中取得了很多成就。

深度学习使得机器去模仿人类的视听行为以及思考，解决许多复杂的模式辨别问题，并且使人工智能的相关技术取得了巨大进步。

5G网络（5G）

NO.1：
The 5th generation mobile communication technology is the latest generation of cellular mobile communication technology,
which is also an extension of 4G , 3G and 2G systems. 5G’s performance
goals are high data rates, reduced latency, energy savings, reduced
costs, increased system capacity, and large-scale device connectivity.

NO1

第五代移动通信技术是最新的蜂窝移动通信技术，它是对4G，3G，2G系统的扩展。

5G的性能目标是高速数据传输，减少延迟，节能，省钱，增加系统容量和设备连接的规模。

SQL定义

NO.1：
Structured Query Language is a
special purpose programming Language, a database query and programming
language for accessing data and querying, updating, and managing
relational database systems.

NO.2：
SQL can be divided into three functional
parts: data definition, data manipulation and data control.The core of
SQL is equivalent to relational algebra, but it has many
features that relational algebra does not, such as aggregation, database
update, and so on.It is a comprehensive, universal, and highly
functional relational database language.

NO1

结构化查询语言是有特殊目的的编程语言，是一种数据库查询。这种编程语言是为了访问数据，查询，更新，管理相关数据库系统而设计

NO2

SQL能够被分成三个功能性的部分：数据定义，数据处理和数据控制。

SQL的核心等同于关系代数，但它拥有许多关系代数没有的特点，比如聚合，数据更新等等。

它是复杂的，广泛的，高功能性的相关数据库语言。

编译器（Compiler）

NO.1：
A compiler is a program that translates
“one language (usually a high-level language)” into “another language
(usually a low-level language).”Advanced computer languages are easy to
write, read, communicate, and maintain.Machine language is something
that a computer can read and run directly.The compiler takes an assembly
or high-level computer language source program as input and translates
it into the equivalent of the machine code in the target language.