Natural Language Processing

Natural Language Processing

What is Natural Language Processing?

Natural Language Processing (NLP) is the ability of computers to understand human language. It is a branch of computer science and a more specific branch of Artificial Intelligence.

NLP is an amalgamation of various technologies combined together like Machine Learning and Deep Learning models. These technologies can process human language in the form of text or voice data to understand its full meaning. They also understand the intent and sentiment of the text

Extracted Insights

Natural Language Processing is categorised based on the extracted insights.

Sentiment Analysis
Identifies and evaluates the text as positive, negative, or neutral.
Topic Modelling
Returns the main topics for each of the documents
Named Entity Recognition
Categorises text and identifies based on different categories like people, country, date, finance, etc.
Regular Expression Matching
A list of text with specific patterns (e.g phone numbers) of characters is searched throughout the text
Semantic Similarity Search
This functionality returns semantically related concepts (and their context) of a word or a set of words searched by the user.

How is NLP useful for your customer's business?

Using NLP technology, vast amounts of textual and unstructured data like text, emails, research results can be processed within seconds. Likewise, people within an organisation can immediately get the full pictures of their documents, without having to read all of them. Finally, the semantic search functionality allows them to quickly find the right information within their corpus of documents.

NLP finds its application for both small and large size businesses dealing with voice or text information analysis. For instance, NLP reduces the overhead of hiring or HRs as the resumes can be initially screened by looking for keywords through NLP models.

Key Benefits of NLP

  • Understanding Data
    Key concepts within the documents are presented to the users making them easier to understand and act accordingly.
  • Eliminate Risks
    Document analytics can be used to identify breaches and can mark sensitive personal information reducing the risk of GDPR breaches.
  • Saves Time
    Large volumes of documents can be received at any given time and documents can be processed effectively.
  • Improve your Business
    With large quantities of documents received, the resulting data can be used in ways not yet considered possible such as customer segmentation or prioritisation of work. For instance, customers’ reviews sentiment analysis can highlight flaws and areas of improvement within the business.
  • Eases Data Classification
    Through named entity extraction and semantic search, data can be easily classified and sorted.
  • Open Source Technology
    NLP open-source libraries are available, reducing running costs and offering high customisation

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In collaboration with our customers, Version 1’s Innovation Labs have built the ‘Smart Action Suite’, a set of enterprise-ready productivity apps focused on addressing common challenges many organisations face, using innovative technologies such as Artificial Intelligence and Robotic Process Automation.
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