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Difference Between Data Mining and Text Mining

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  • Last Updated : 30 Sep, 2022
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Data Mining: 
Data mining is the process of finding patterns and extracting useful data from large data sets. It is used to convert raw data into useful data. Data mining can be extremely useful for improving the marketing strategies of a company as with the help of structured data we can study the data from different databases and then get more innovative ideas to increase the productivity of an organization. Text mining is just a part of data mining. 

Text Mining: 
Text mining is basically an artificial intelligence technology that involves processing the data from various text documents. Many deep learning algorithms are used for the effective evaluation of the text. In text mining, the data is stored in an unstructured format. It mainly uses the linguistic principles for the evaluation of text from documents. 



Below is a table of differences between Data Mining and Text Mining: 

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S.No.Data MiningText 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.Statistical 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.
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