Application and Future of NLP

by ShehrBano

Application and Future of NLP

In our bustling life we use a bunch of different technologies without even realizing or giving a thought to it. One of these technologies has become a very pervasive and hot topic recently, as world now hinges upon automation for a number of day to day activities. You must have heard the words Natural Language Processing from the perspective of Artificial Intelligence. Let's see how it’s making things easier for us.

What is NLP?

NLP is a branch of computer linguistics that empowers computer programs to analyze, interpret and derive meaning from the speech and text which are a form of human language. Emotions like excitement, sarcasm, sadness are difficult to delineate and analyze. But NLP has eliminated this issue. Its unique ability to decipher the natural language by machines have greatly reduced the need for manpower. NLP has become facile over the years. Companies have vast amount of data in the form of texts messages, audios, emails or videos which they receive from different communication channels. When you analyze this large amount of data your algorithms improve in terms of functioning.

There are several techniques that are involved in the better functioning of NLP, that have decreased the time to process the information by discarding or omitting inessential elements and simplifying the sentences. These techniques have also helped companies to achieve their objectives:

1. Sentiment Analysis

In this technique, sentences and statements are examined on the basis of sentiments or emotions. According to this analysis, human verbal and written communication in the form of sentences is assessed by looking at whether a specific chunk of the sentence elicits a positive, neutral or a negative response towards a certain subject. Marketers frequently use this technique in order to see the attitudinal response of consumers towards products, brands, campaigns, events etc. Advanced algorithms are more receptive in perceiving and recognizing emotions behind the sentences such as fear, anger, excitement, happiness or sadness etc.

2. Parsing

In this method the sentences are broken down into simpler form to deduce the meaning. By analyzing the words and their relationship with one another the algorithms are able to tell about their structure.  

3. Relationship Extraction

In this process, certain entities are fished out from a statement or a sentence to establish a semantic relationship between them. If you want to know something such as the "Products offered by Outfitters", you simply search it on Google and the right answer will appear on your screen. All this is done by using relationship extraction technology, the algorithm picks out the words such as "products" and "outfitters", forms a link between them and gives you a list of products that the company offers.

The NLP technology is used in several fields and provides a fast and efficient customer service while cutting down cost. Let’s look at its usefulness in terms of data science.

1. Forecasting the spread of disease

NLP technology has served the healthcare sector by detecting illnesses and anticipating the spread of impending diseases. By decoding the speech patterns, it gives a clear knowledge to medical practitioners regarding illness related progression (e.g. post-traumatic stress disorder or depression etc.). This helps doctors to better understand their patients and their predicament.

2. E commerce

Competition is rising in e commerce and companies must ponder over creative solutions to deal with the inefficiencies that occur while tending to their customers. They can use sentiment analysis tool to look for products that best satisfy their customer. Moreover, through the help of NLP they can go through the internet data to check their platform's performance. They can offer hyper personalized communication to their customers on the basis of social media listening.

3. Language translators

You can translate the online text in different languages and all this is not possible without NLP tool. One example is of Google translator that translates and converts pages into any language, eliminating the language barrier.

In short, NLP is picking pace and providing a unique form of interaction between humans and machines. You can take the example of Apple's Siri that provide virtual assistance, enabling you to make calls or send text messages through verbal communication. According to a study around 75% of the business owners want to adopt and change the way they operate in order to align themselves with the changing customer needs. Many are incorporating NLP models to interact and quickly respond to their customers, so there is no doubt that progress is being made in this technology.