4 Natural Language Processing Applications and Examples for Content Marketers

For example, a tool might pull out the most frequently used words in the text. Another example is named entity recognition, which extracts the names of people, places and other entities from text. Three tools used commonly for natural language processing include Natural Language Toolkit , Gensim and Intel natural language processing Architect. NLTK is an open source Python module with data sets and tutorials. Gensim is a Python library for topic modeling and document indexing.

But those individuals need to know where to find the data they need, which keywords to use, etc. NLP is increasingly able to recognize patterns and make meaningful connections in data on its own. It uses large amounts of data and tries to derive conclusions from it.

Spam detection

But this isn’t the text analytics tool for scaling your content or summarizing a lot at once. To do that, the app has to be taught to understand the accent and language patterns of a given celebrity to generate believable language. Like all GPS apps, it comes with a standard female voice that guides you as you drive. But you can also Examples of NLP download voice packs of famous people like Arnold Schwarzenegger and Mr. T to make your drive just a bit more entertaining. 😉 But seriously, when it comes to customer inquiries, there are a lot of questions that are asked over and over again. Machines are still pretty primitive – you provide an input and they provide an output.

They also help in areas like child and human trafficking, conspiracy theorists who hamper security details, preventing digital harassment and bullying, and other such areas. But, the problem arises when a lot of customers take the survey leading to increasing data size. It becomes impossible for a person to read them all and draw a conclusion.

Semantic Analysis

Natural language processing helps the Livox app be a communication device for people with disabilities. The creation of Carlos Pereira, a father who developed the app to help his non-verbal daughter, who has cerebral palsy communicate, the customizable app is now available in 25 languages. These are the top 7 solutions for why should businesses use natural language processing and the list is never-ending. Hence, it is an example of why should businesses use natural language processing.

HootSuite is a social media management platform that includes sentiment analysis as part of its tracking functionality. Once you’ve posted content, Hootsuite will track it for the usual analytics as well as positive or negative reactions to your content. In many ways, the models and human language are beginning to co-evolve and even converge. As humans use more natural language products, they begin to intuitively predict what the AI may or may not understand and choose the best words.

Natural Language Processing

Natural language processing is a form of AI that extracts meaning from human language to make decisions based on the information. This technology is still evolving, but there are already many incredible ways natural language processing is used today. Here we highlight some of the everyday uses of natural language processing and five amazing examples of how natural language processing is transforming businesses. Google, Yahoo, Bing, and other search engines base their machine translation technology on NLP deep learning models. It allows algorithms to read text on a webpage, interpret its meaning and translate it to another language.

NLP algorithms may miss the subtle, but important, tone changes in a person’s voice when performing speech recognition. The tone and inflection of speech may also vary between different accents, which can be challenging for an algorithm to parse. Doing right by searchers, and ultimately your customers or buyers, requires machine learning algorithms that are constantly improving and developing insights into what customers mean and what they want. While computers communicate with one another in code and long lines of ones and zeros, they’ve come to better understand human language with natural language processing and machine learning .

What is Natural Language Processing (NLP)?

As companies adopt measures to improve sustainability goals, enterprise applications can play a key role. Although there are doubts, natural language processing is making significant strides in the medical imaging field. Learn how radiologists are using AI and NLP in their practice to review their work and compare cases.

• One such sub-domain of AI that is gradually making its mark in the tech world is Natural Language Processing .
• It is all most same as solving the central artificial intelligence problem and making computers as intelligent as people.
• Consumers can describe products in an almost infinite number of ways, but e-commerce companies aren’t always equipped to interpret human language through their search bars.
• Predictive text and its cousin autocorrect have evolved a lot and now we have applications like Grammarly, which rely on natural language processing and machine learning.
• Another way to handle unstructured text data using NLP is information extraction .
• Great Learning’s Blog covers the latest developments and innovations in technology that can be leveraged to build rewarding careers.