15 Natural Language Processing Examples we didn't know existed
1. Streamlining Patient Information
In maximum clinics, patients report their symptoms to a nurse or office, and the person records what they have shared with the health practitioner. Clinics and medical businesses have now started out the use of NLP to simplify affected person information and automate the process of understanding sufferers’ conditions. Now businesses have resources like
98point6 computerized assistant, which uses NLP to allow sufferers to share their information. Before their appointment with the medical doctor, an affected person is virtually required to text their medical records/conditions to the app. It might then streamline the information, passing it directly to the health practitioner.
2. Smart Home Devices
Smart Home Devices like Alexa and Google Home are becoming immensely popular, particularly amongst more youthful consumers. These smart home devices are top notch for multitasking. Suppose you want to play music however have your fingers preparing dinner. In that case, you could truly coach Google Home to include your favorite playlist, and you’re done. Here, your smart home device makes use of NLP to recognize your voice instructions and take suitable action. When giving a voice command on your smart assistant (like Google Assistant or Siri), NLP also works behind the curtain so that your
assistant understands your instructions.
3. Messenger or Chatbots
Many corporations these days use messenger apps coupled with social media, to deliver connect and engage with customers. Facebook Messenger is one of the greater recent systems used for this purpose. In this example, NLP enables expansion in the use of computerized respond to systems so they not only market a product or service however can also completely engage with customers. The greater comfortable the service is, the more people are probable to use the app. Uber took gain of this concept and evolved a Facebook Messenger chatbot, thereby creating a new source of sales for themselves.
4. Social Media Monitoring
Monitoring and assessment of what clients are saying about a brand on social media can assist corporations determine whether to adjust in brand or retain as it is. NLP makes this system automated, faster, and more accurate. Social media listening tool such as Sprout Social assist screen,examine, and analyze social media activity concerning a particular brand.
5. Data Analysis
Natural language capabilities are being included into data analysis workflows as more BI providers provide a natural language interface to data visualizations. One example is smarter visible encodings, providing the best visualization for the proper assignment primarily based at the semantics of the information. This opens extra opportunities for humans to explore their data usage of natural language statements or question fragments made from several key phrases that can be interpreted and assigned a meaning. Applying language to analyze records not only enhances the extent of accessibility, however, lowers the barrier to analytics throughout organizations, beyond the anticipated community of analysts and software program developers.
6. Email Filters
Email filters are one of the maximum primary and initial packages of NLP online. It commenced out with spam mail filters, uncovering certain phrases or terms that signal a junk mail message. But filtering has upgraded, much like early adaptations of NLP. One of the greater widespread, more modern applications of NLP is determined in Gmail’s email category. The device recognizes if emails belong in one among 3 classes (primary, social, or promotions) based totally on their contents. For all Gmail users, this continues your inbox to a doable length with crucial, applicable emails you desire to check and reply to quickly.
7. Algorithmic Training
People additionally comprehend it as “Automated Trading” or “Black Box Trading”. It essentially involves the use of an algorithm to execute buying and selling transactions. Algorithmic buying and selling takes place on two levels initially. At the primary level, customers can define suggestions (relevant to time, price, and volume) that the program can use to execute a transaction. For instance, in case you say you want to shop for three levels of Tesla stock whilst the stock price drops to $1,500, the program can comply with your instructions. Algorithmic buying and selling also can involve the use of robo-advisors to create portfolio optimization tips at a higher level. The application examines myriad data affecting financial markets (along with the monetary performance of businesses, reviews on mergers and acquisitions, etc.), imparting suggestions on what an investor should buy or sell. NLP performs a crucial role in assisting such programs make sense of an unimaginable amount of data and information.
8. Personalized Customer Experience (CX)
The digital age has made many aspects of our everyday lives less difficult. As a result, consumers expect much more from interacting with their brand, particularly with regards to customization. Media corporations suffering to keep their subscriptions and readership have determined this of interest, particularly selecting NLP as their savior. Expert.ai’s NLP platform lets in publishers and content manufacturers to automate critical categorization and metadata records through tagging, creating readers’ greater thrilling and personalized reports. The media also can have content recommendations so that users can see only the content that is most relevant to them.
9. Survey Analytics
One of the best ways for NLP to enhance insight and company experience is by analyzing data for key-word frequency and trends, which tend to signify usual consumer sentiment about a brand. Even though the name, IBM SPSS Text Analytics for Surveys is one of the best software out there for analyzing almost any unfastened text, no longer simply surveys. One reviewer examined the device by way of using his Twitter archive as an input.
10. Monitor and Analyze Feedback
Between social media, critiques, contact form, support tickets, and different varieties of communication, customers are continuously leaving feedback about the products or services. NLP can assist mixture and make sense of all that remarks, turning it into actionable insight that may assist improve the enterprise. Wonderflow’s Useful Reviews tab inside The Wonderboard, is beneficial for reading usual feedback. In this area, you could view your maximum useful reviews. Wonderflow will then highlight the advantageous and bad statements in those evaluations so you can quickly distill this data and evaluate how every of your products or services are perceived by customers Recently, Wonderflow was selected by independent research firm Aragon Research as one of the companies making an impact in document analytics.
11. Automatic Insights
Automatic insights are the following step in NLP applications. This feature does no longer simply examine or discover patterns in a collection of free content but also can deliver insights about a service or product performance that mimics human speech. In other phrases, let us say someone has a query like “what is the most giant disadvantage of the use of freeware?”. In
this case, the software will deliver the correct reaction based on data about how others have answered to a comparable query.
12. Improve User Experience
NLP can be integrated with a website to provide an extra r-friendly experience. Features like spell check, autocomplete, and autocorrect in search bars can make it less difficult for customers to locate the information they’re looking for, which in turn continues them from navigating far from your web page.
13. A Source of Intelligence
Mounds of IoT information are continuously accrued from the gadgets and interfaces we use each day. Walmart alone is predicted to accumulate more than 2.5 petabytes of information every hour from its customer interactions. Once all this data is collected, the artificial intelligence aspects of NLP are used to procedure and make sense of it. Better nonetheless, this information gets processed at a scale and speed that greatly exceeds that of your average person. NLP augments the abilities of human teams, giving organizations a fast-questioning competitive part. Machines with language information competencies also can train us a thing or two, even offer shops a fresh perspective. An organization that has been in the custom business for years got the idea to organize all ‘Dracula costumes’ right into a separate category page, based totally on the idea of an algorithm.
14. Digital Phone Cells
We all hear “this call can be recorded,” but hardly ever do we surprise what that entails. Turns out, those recordings can be used for training functions, if a person is aggrieved, but most of the time, they pass into the database for an NLP system to examine and improve in the future. Automated systems direct customer calls to a service consultant or online chatbots, which respond to customer requests with helpful information. This is an NLP exercise that many companies, which includes big telecommunications providers have placed to apply. NLP enables computer-generated language close to the voice of a human. Phone calls to schedule appointments like an oil trade or haircut may be automated.
15. Content Generation
AI-based content material generation, or content material this is generated via a computer application and not a human, has been the focal point of much interest in current years. This form of era ambitions to create customized content for each purchaser or reader without the usage of personal information about them. In a world in which human beings have such a
lot of distinct tastes and possibilities, it can be difficult to please everybody. The Muse Content Generation device may be used to create content for an extensive variety of uses. They have a live demo part in which they showcase some of their equipment. The AI-Based content generation field has many possibilities. The specific area f study which deals with such content
generation is Natural Language Generation.