AI（人工智能）的数据是如何采集的？
（一）AI（人工智能）的数据处理
1、结构化数据：结构化数据是指可以在表格或类似格式中存储的数据。这些数据通常包括数字、日期、价格或标签等类型的数据。结构化数据通常来自数据库或企业应用程序中的信息，并且可以根据预定义的程序轻松提取和分析。 数字化转型网www.szhzxw.cn
2、半结构化数据：半结构化数据是指不使用标准数据模式但具有一定的结构化元素的数据。例如，XML文件和HTML文档等数据格式都具有一定的结构和标记，可以通过解析和处理工具进行分析。
3、非结构化数据：非结构化数据是指缺乏明确结构的文本和媒体文件，如电子邮件、视频、音频、图像和社交媒体帖子等。这些数据通常不适合存储在标准的结构化数据库中，并需要特殊的处理技术。
（二）AI（人工智能）的数据来源
1、传感器数据：传感器数据通常来自物联网设备，诸如温度、湿度、加速度、压力等等。这些数据可以用于监测物理环境和系统性能，并通过机器学习应用来进行分析和预测。
2、网络数据：网络数据是指通过互联网公开获取的信息。例如，社交媒体、博客、新闻文章和电子邮件等内容，通常是使用Web爬虫或API提取的。 数字化转型网www.szhzxw.cn
3、企业数据：企业数据包括各种类型的结构化和半结构化数据，例如交易记录、客户信息和产品信息等。这些数据通常存储在企业数据库中，可以通过SQL或其他技术进行查询和分析。
（三）AI（人工智能）的外部数据
外部数据是指与企业或组织无关的数据集。例如，政府数据、气象数据、地理数据、人口统计数据等等。这些数据通常由政府或其他机构发布，并且可用于模型精度提高或新业务机会的发掘。
总体来说，数据的种类和来源是多种多样的，人工智能（AI）的应用需要根据不同的数据特点来选择适当的数据收集和处理方法，以便在建立模型时能获得最好的结果。
数字化转型网人工智能专题
与全球关注人工智能的顶尖精英一起学习！数字化转型网建立了一个专门讨论人工智能技术、产业、学术的研究学习社区，与各位研习社同学一起成长！欢迎扫码加入！ 数字化转型网www.szhzxw.cn
本文由数字化转型网（www.szhzxw.cn）转载而成，来源于网络；编辑/翻译：数字化转型网宁檬树。
翻译：
How is AI (Artificial intelligence) data collected?
1. AI (Artificial intelligence) data processing
(1) Structured data: Structured data refers to data that can be stored in tables or similar formats. This data usually includes types of data such as numbers, dates, prices, or labels. Structured data typically comes from information in databases or enterprise applications and can be easily extracted and analyzed according to predefined procedures. 数字化转型网www.szhzxw.cn
(2) Semi-structured data: Semi-structured data refers to the data that does not use the standard data model but has certain structured elements. For example, data formats such as XML files and HTML documents have certain structures and tags that can be analyzed by parsing and processing tools.
(3) Unstructured data: Unstructured data refers to text and media files that lack a clear structure, such as emails, videos, audio, images, and social media posts. This data is usually not suitable for storage in standard structured databases and requires special processing techniques.
2. Sources of AI (Artificial intelligence) data
(1) Sensor data: Sensor data usually comes from iot devices, such as temperature, humidity, acceleration, pressure, and so on. This data can be used to monitor the physical environment and system performance, and can be analyzed and predicted through machine learning applications.
(2) Network data: Network data refers to information publicly available through the Internet. For example, content such as social media, blogs, news articles, and emails are often extracted using Web crawlers or apis. 数字化转型网www.szhzxw.cn
(3) Enterprise data: Enterprise data includes various types of structured and semi-structured data, such as transaction records, customer information and product information. This data is usually stored in enterprise databases and can be queried and analyzed through SQL or other technologies.
3. External data of AI (artificial intelligence)
External data refers to data sets that are not associated with a business or organization. For example, government data, meteorological data, geographic data, demographic data, and so on. This data is usually published by governments or other agencies and can be used to improve model accuracy or identify new business opportunities. 数字化转型网www.szhzxw.cn
In general, the types and sources of data are diverse, and the application of artificial intelligence (AI) needs to select appropriate data collection and processing methods according to different data characteristics in order to obtain the best results when building models.
