数据挖掘和文本挖掘的区别

数据挖掘：
数据挖掘是从大数据集中寻找模式和提取有用数据的过程。它用于将原始数据转换为有用的数据。数据挖掘对于改进公司的营销策略非常有用，因为在结构化数据的帮助下，我们可以研究来自不同数据库的数据，然后获得更多创新想法以提高组织的生产力。文本挖掘只是数据挖掘的一部分。

文本挖掘：
文本挖掘基本上是一种人工智能技术，涉及处理来自各种文本文档的数据。许多深度学习算法用于对文本进行有效评估。在文本挖掘中，数据以非结构化格式存储。它主要使用语言学原理来评估文档中的文本。

下表列出了数据挖掘和文本挖掘之间的差异：

S.No.	Data Mining	Text Mining
1.	Data mining is the statistical technique of processing raw data in a structured form.	Text mining is the part of data mining which involves processing of text from documents.
2.	Pre-existing databases and spreadsheets are used to gather information.	The text is used to gather high quality information.
3.	Processing of data is done directly.	Processing of data is done linguistically.
4.	Stastical techniques are used to evaluate data.	Computational linguistic principles are used to evaluate text.
5.	In data mining data is stored in structured format.	In text mining data is stored in unstructured format.
6.	Data is homogeneous and is easy to retrieve.	Data is heterogeneous and is not so easy to retrieve.
7.	It supports mining of mixed data.	In text mining, mining of text is only done.
8.	It combines artificial intelligence, machine learning and statistics and applies it on data.	It applies pattern recognizing and natural language processing to unstructured data.
9.	It is used in fields like marketing, medicine, healthcare.	It is used in fields like bioscience and customer profile analysis.