Text Analytics vs NLP

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Text Analytics, also known as Text Mining, is an approach and a method to extract value, actionable information and insights from text data. It uses NLP and Information Retrieval techniques to convert unstructured data into structured form that can further be used for analysis, deriving patterns and insights from this data that would be helpful for the end user.

Applications

  • Social Media Analysis
  • Fraud Detection
  • Spam Filtering

Natural Language Processing (NLP) it allows computers and machines to perform task like read and understanding human language. It uses different algorithms to interpret human language.
It is primarily used for designing and building applications that allow interaction between machines and languages evolve by humans.

Applications

  • Machine Translation
  • Speech Recognition System
  • Question Answering Systems

Difference between NLP and Text Analytics

Text Analytics/Mining involves text itself, whereas NLP includes text structure and metadata. Finding count of words, stemming of words, identify grammar like noun/verb, length of sentences… this is text mining. Processing of these things is NLP like finding sentence sentiment.


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