10 Amazing Examples Of Natural Language Processing

This makes for fun experiments where individuals will share entire sentences made up entirely of predictive text on their phones. The results are surprisingly personal and enlightening; they’ve even been highlighted by several media outlets. Monitoring and evaluation of what customers are saying about a brand on social media can help businesses decide whether to make changes in brand or continue as it is. Social media listening tool such as Sprout Social help monitor, evaluate and analyse social media activity concerning a particular brand. The services sports a user-friendly interface does not require a ton of input for it to run. Many companies today use messenger apps coupled with social media, to deliver connect and interact with customers.

Imagine the power of an algorithm that can understand the meaning and nuance of human language in many contexts, from medicine to law to the classroom. As the volumes of unstructured information continue to grow exponentially, we will benefit from computers’ tireless ability to help us make sense of it all. Natural language processing helps computers communicate with humans in their own language and scales other language-related tasks.

Understanding Natural Language Processing (NLP):

Their NLP apps can process unstructured data using both linguistic and statistical algorithms. Human language is filled with ambiguities that make it incredibly difficult to write software that accurately determines the intended meaning of text or voice data. ​Government agencies are awash in unstructured and difficult to interpret data. To gain meaningful insights from data for policy analysis and decision-making, they can use natural language processing, a form of artificial intelligence.

This allows algorithms to understand and sort data found in customer feedback forms. London based Personetics have used natural language processing to develop the Assist chatbot. Properly applied natural language processing is an incredibly effective application.

What Is Natural Language?

Natural Language Processing (NLP) is at work all around us, making our lives easier at every turn, yet we don’t often think about it. From predictive text to data analysis, NLP’s applications in our everyday lives are far-ranging. This article is part of a series I write about NATURAL programming.

First, we are going to open and read the file which we want to analyze. TextBlob is a Python library designed for processing textual data. Gensim is an NLP Python framework generally used in topic modeling and similarity detection. It is not a general-purpose NLP library, but it handles tasks assigned to it very well.

In the sentence above, we can see that there are two “can” words, but both of them have different meanings. The second “can” word at the end of the sentence is used to represent a container that holds food or liquid. Natural Language Processing allows your device to hear what you say, then understand the hidden meaning in your sentence, and finally act on that meaning. But the question this brings is What exactly is Natural Language Processing?

From automatic translation or sentence completion to identify insurance fraud and powering chatbots, NLP is increasingly common. Spam detection removes pages that match search keywords but do not provide the actual search answers. Natural Language Processing is what computers and smartphones use to understand our language, both spoken and written.

Applications of Natural Language Processing

At your device’s lowest levels, communication occurs not with words but through millions of zeros and ones that produce logical actions. To learn a new language, you should practice it daily, whether it’s a human or programming language. Numerous programming languages have been developed during the history of computers for various development purposes. Each programming language has its collection of keywords and a distinct syntax for arranging the instructions for the software. If a particular word appears multiple times in a document, then it might have higher importance than the other words that appear fewer times (TF).

• The NLP algorithm is trained on millions of sentences to understand the correct format.
• This means that it can be difficult, and time-consuming to process and translate into useful information.
• The COPD Foundation uses text analytics and sentiment analysis, NLP techniques, to turn unstructured data into valuable insights.
• Lenddo applications are helping lenders better assess applicants, meaning that millions of more people are able to safely and responsibly access credit.
• NLP is able to quickly analyse and derive useful intelligence from both structured and unstructured data sets.

A similar study saw researchers developing natural language processing tools to link medical terms to simple definitions. Utilising natural language processing effectively enables humans to easily communicate with computer technology. Language is a method of communication with the help of which we can speak, read and write. (NLP) is a subfield of Computer Science that deals with Artificial Intelligence (AI), which enables computers to understand and process human language. Online chatbots, for example, use NLP to engage with consumers and direct them toward appropriate resources or products.

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