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Text mining, also referred to as text data mining, roughly equivalent to text analytics, is the process of deriving high-quality information from text. High-quality information is typically derived through the devising of patterns and trends through means such as statistical pattern learning.
What is text mining and how does it work?
Text mining, also known as text analysis, is the process of transforming unstructured text into meaningful and actionable information. By identifying topics, patterns, and relevant keywords, text mining allows you to obtain valuable insights without needing to go through all your data manually.
What is the difference between data mining and text mining?
While data mining handles structured data – highly formatted data such as in databases or ERP systems – text mining deals with unstructured textual data – text that is not pre-defined or organized in any way such as in social media feeds.
What is text mining used for?
Widely used in knowledge-driven organizations, text mining is the process of examining large collections of documents to discover new information or help answer specific research questions. Text mining identifies facts, relationships and assertions that would otherwise remain buried in the mass of textual big data.
How does text analysis work?
Text Analysis is about parsing texts in order to extract machine-readable facts from them. The purpose of Text Analysis is to create structured data out of free text content. The process can be thought of as slicing and dicing heaps of unstructured, heterogeneous documents into easy-to-manage and interpret data pieces.
What is text mining and how can we use it?
Text mining, also referred to as text data mining, roughly equivalent to text analytics, refers to the process of deriving high-quality information from text. High-quality information is typically derived through the devising of patterns and trends through means such as statistical pattern learning. See the full article for more details.
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