Natural language processing (NLP) is a modern day intelligent system in which natural language is used as a communication medium. The main objective of NLP is to make computers do the profound tasks with the natural language. NLP has become a key subset of AI like humanoids required to do a specific task as per our instruction be it speech or text. The key aspect of NLP is to understand the context and aspect of language given as input and map it with respective useful representation. Few key NLP applications in today’s world are:

1) Language translation software

2) Chat-bots

3) Search engines

4) Speech assistant

5) Monitoring social media

Why is NLP important?

World revolves around data and it’s our responsibility to generate insights from it. Everyday millions of unstructured and unorganized data are generated from millions of tweets, emails and web searches.

NLP plays a vital role in structuring the huge chunk of data by preparing the text and speech for machines so that they’re able to interpret, process, and organize information. These insights are key to any business and help in multiple ways.

Techniques of NLP

There are various techniques in NLP and few are explained below:-

  • Bag of Words

Bag of words is used to extract all the features from a text document and also preprocesses the text. It explains the occurrence of the words within a document (corpus). It is mainly used for featuring generation from text data.

Example:

Sai is fond of India and he hates football

Ram loves football

Above given two statements (corpora) are taken as documents and we treat both the documents as a separate entity. Then we make a list of all the words present in both the documents except punctuation’s as here,

“Sai”, “is”, “fond”,” of”, “India”, “he”, “hates”, “football”, “Ram”,” loves”

Then we create these documents into vectors (vectorization in ML) for further modelling.

1st statement vector form [1, 1, 0, 1, 1, 0, 1, 0, 1]

2nd statement vector form  [1,1,0,0,1,0,0,1,1]

  • Sentiment Analysis

Sentiment analysis is a technique used to find the emotion and feeling from a text. The basic task of Sentiment analysis is to find opinions in any document, sentence, text, social media and reviews are positive, negative, or neutral.

Generally, objective text data are either statements or facts which does not represent any emotion or feeling. It is advisable to use sentiment analysis on subjective data since it is written by humans showing emotions and feelings.

Best example of this could be finding the reaction of customers when a new product is launched, political campaigning, social media trend etc.

  • Aspect Mining

Aspect mining is a key technique in conjunction with part of speech tagging. When this is used with sentiment analysis, it extracts complete information from the text.

Aspects & Sentiments:

  • Customer care – negative
  • Call center – negative
  • Agent – negative
  • Pricing/Premium – positive
  • Topic Modelling

Topic modeling is one of the most complicated technique to identify natural topics in the text. A prime advantage of topic modeling is that it is an unsupervised technique. In most places the data would be unsupervised and it is important to classify them into the labels which we find.

The most common technique which can be used to find the labels from the text would be LDA. However few clustering techniques can also be done but the output wouldn’t be as good as LDA.

The concept of LDA is that each text document comprises of several topics and each topic comprises of several words. The input required by LDA is merely the text documents and the expected number of topics.

  • Named Entity Recognition

This is the most basic and commonly used technique in NLP which primarily deals with extraction of entities in the text. It highlights the fundamental concepts and references in the text. Named entity recognition identifies entities such as people, locations, organizations, dates, etc. from the text. NER is based on grammar rules and supervised models.

Examples:-

Person: Sachin Tendulkar,Virat Kohli

Location: India, United States

Date: Last month, 2020

Organization: AiNxt