See this simple introduction to Natural Language Processing (NLP)

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Today, with Digitization of everything, 80 percent the data being created is unstructured.

Audio, Video, our social footprints, the data generated from conversations between customer service reps, tons of legal document’s texts processed in financial sectors are examples of unstructured data stored in Big Data.

Organizations are turning to natural language processing (NLP) technology to derive understanding from the myriad of these unstructured data available online and in call-logs.

Natural language processing (NLP) is the ability of computers to understand human speech as it is spoken. It is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Machine Learning has helped computers parse the ambiguity of human language.

Apache OpenNLP, Natural Language Toolkit(NLTK), Stanford NLP are various open source NLP libraries used in real world application below.

Here are multiple ways NLP is used today:

The most basic and well known application of NLP is Microsoft Word spell checking.

Text analysis, also known as sentiment analytics is a key use of NLP. Businesses are most concerned with comprehending how their customers feel emotionally adn use that data for betterment of their service.

Email filters are another important application of NLP. By analyzing the emails that flow through the servers, email providers can calculate the likelihood that an email is spam based its content by using Bayesian or Naive based spam filtering.

Call centers representatives engage with customers to hear list of specific complaints and problems. Mining this data for sentiment can lead to incredibly actionable intelligence that can be applied to product placement, messaging, design, or a range of other use cases.

Google and Bing and other search systems use NLP to extract terms from text to populate their indexes and to parse search queries.

Google Translate applies machine translation technologies in not only translating words, but in understanding the meaning of sentences to provide a true translation.

Many important decisions in financial markets use NLP by taking plain text announcements, and extracting the relevant info in a format that can be factored into algorithmic trading decisions. E.g. news of a merger between companies can have a big impact on trading decisions, and the speed at which the particulars of the merger, players, prices, who acquires who, can be incorporated into a trading algorithm can have profit implications in the millions of dollars.

Since the invention of the typewriter, the keyboard has been the king of human-computer interface. But today with voice recognition via virtual assistants, like Amazon’s Alexa, Google’s Now, Apple’s Siri and Microsoft’s Cortana respond to vocal prompts and do everything from finding a coffee shop to getting directions to our office and also tasks like turning on the lights in home, switching the heat on etc. depending on how digitized and wired-up our life is.

Question Answering – IBM Watson is the most prominent example of question answering via information retrieval that helps guide in various areas like healthcare, weather, insurance etc.

Therefore it is clear that Natural Language Processing takes a very important role in new machine human interfaces. It’s an essential tool for leading-edge analytics & is the near future.

Sandeep Raut

7th Rank in Global Top 100 Digital Transformation Influencers Delivered speech at India Analytics & Big Data Summit at Bangalore on "How Machine Learning is helping in Digital Transformation" on 4th Feb 2016 Delivered Thought Leadership speech at Unicom - India Analytics & Big Data Summit on "Big Data Analytics disrupting industry" Delivered speech at IIT Mumbai on "Analysing Big data for disruptive innovation" Delivered a keynote speech at Rizvi College of Engineering on "Fraud Detection & Prevention using Analytics" • Director for Digital Transformation in Syntel. • Has more than 29 years of IT Services / Consulting / Off-shoring experience • Over 18 years in Business Intelligence space. • Had helped organizations in establishing the BI-Analytics Services CoEs. • Had spearheaded several marquee accounts and was significantly instrumental in building new business for the practice as well. • Had successfully initiated, mentored & deployed various strategic consulting services & solutions like Digital Transformation, BI Strategy Planning, BI Offshorization, BI Development/Deployment, Campaign Management, Inventory Optimization which resulted into multi-million dollar business. • Had developed & managed Customer relations with Global players across USA, UK & Asia Pacific. Specialties: Digital Transformation, BI & Big Data Analytics Banking and Financial Services, Healthcare LifeSciences, Insurance, Retail Manufacturing - Supply Chain Management

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