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Text Mining:
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. Text mining usually involves the process of structuring the input text, deriving patterns within the structured data, and finally evaluation and interpretation of the output.
Text mining, which is sometimes referred to “text analytics”, is one way to make qualitative or “unstructured” data usable by a computer. 
Text mining is the analysis of data contained in natural language text.
The application of text mining techniques to solve business problems is called text analytics.
» Text mining can help an organization derive potentially valuable business insights from text-based content such as word documents, email etc.,
» Text mining tasks include text categorization, text clustering, concept/entity extraction, production of granular taxonomies, sentiment analysis, document summarization, and entity relation modelling (i.e., learning relations between named entities).
» Text mining as the process or practice of examining large collections of written resources in order to generate new information, typically using specialized computer software. It is a subset of the larger field of data mining.
» Text analytics software can help by transposing words and phrases in unstructured data into numerical values which can then be linked with structured data in a database and analyzed with traditional data mining techniques.
» It is also known as Knowledge Discovery in Text (KDT), refers generally to the processing of extracting interesting and nontrivial information from unstructured text.
Block Diagram:
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  • Enterprise Business Intelligence/Data Mining, Competitive Intelligence
  • E-Discovery, Records Management
  • National Security/Intelligence
  • Scientific discovery, especially Life Sciences
  • Sentiment Analysis Tools, Listening Platforms
  • Natural Language/Semantic Toolkit or Service
  • Publishing
  • Automated ad placement
  • Search/Information Access
  • Social media monitoring
Real Time Examples:
» Text Mining Software and concepts are avail from many commercial and open source companies and sources.
  • AeroText
  • Angoss
  • Attensity
  • Autonomy
  • Clarabridge
  • IBM LanguageWare
Open Source:
  • QueryTermAnalyzer
  • Carrot2
  • GATE
  • OpenNLP
  • Natural Language Toolkit
  • RapidMiner
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