Language is an important part of how we communicate with each other. It’s the same with technology.
At the intersection of these two things is natural language processing (NLP), which breaks a language into a format that both computers and people can understand and use.
NLP services can be provided by AI and technology companies, as well as consulting firms that specialize in NLP solutions.
These services can include chatbot development, machine translation, sentiment analysis, information retrieval, and text summarization.
The definition of Natural Language Processing
Natural Language Processing (NLP) is an artificial intelligence that helps computers understand, interpret, and work with human languages like English and Hindi to figure out what they mean.
NLP helps developers organize and structure knowledge to translate, summaries, recognize named entities, extract relationships, recognize speech, divide topics, etc.
NLP is becoming just as popular as AI because AI is being used more and more. You might not realize it, but NLP technology is all around us and affects our daily lives in many ways.
Here are a few of the most common ways to use it.
If you’ve used an email account in the last 10 years, you’ve gotten something out of NLP technology.
Once an algorithm has been trained enough on email text data, it can identify, classify, and label emails as regular, spam, or malicious emails.
Usually, malicious emails are deleted from your account before you see them. In the same way, different email providers may use different types of email filters, such as social or promotional.
Even the business world is starting to see how useful this technology is, as 35 per cent of company’s surveyed use NLP to classify emails or texts.
Also, strong email filtering at work can make it much less likely that someone will click on and open a malicious email, keeping sensitive information from getting out.
For many years, the results could always have been clearer and more offensive when you tried to translate a sentence from one language to another.
This happened so often that many asked if it would ever be possible to translate the text correctly.
Thanks to AI and NLP, algorithms can be trained on texts in different languages, making it possible to get the same meaning in another language.
Even languages that aren’t Romance, like Russian and Chinese, can use this technology. These languages are usually harder to translate because they have different alphabets and use characters instead of letters.
People now search for information online more than any other way. Because of this, more companies realize how important it is to add NLP search to their software.
Google just put out a new search engine that helps people find answers to complicated questions like “How should I get ready to climb K2?” in text or a picture.
In the same way, top NLP companies like expert.ai use search to their advantage. Using an AI-powered cognitive search engine, customers can make custom enterprise search solutions, such as ones that let you search for documents related to a certain topic or via a message.
For example, the keyword “car” would also bring up documents about SUVs, station wagons, and corvettes since these things have something to do with “cars.”
Smart assistants like Siri, Alexa, and Cortana are becoming increasingly important in our lives. This is a good example of NLP. Using NLP, they break language into parts of speech; word stems, and other linguistic features.
The rest is taken care of by natural language understanding (NLU), which lets machines understand language, and natural language generation (NLG), which lets machines “speak.” This should get you the answer you want.
Another type of smart assistant that works the same way is a Chabot powered by natural language processing (NLP).
Instead of using voice recognition, they respond to text input from customers. Given how useful they are as sources of information, most online companies now use them as their main way to communicate on their website.
The Digital Age has made many things easier for us to do in our daily lives. Because of this, customers have much higher expectations of how brands interact with them, especially when it comes to personalization.
Media companies, which have been having trouble keeping readers and subscribers, have noticed this and are turning to NLP to help.
Expert.ai’s Natural Language Processing (NLP) platform lets publishers and content creators use tags to automate important categorization and metadata information, giving readers a more engaging and personalized reading experience.
Media outlets can also suggest content so that users only see what is most important to them.
Many companies have so much data that they need help figuring out what to do with it, which makes it hard to get useful insights. Because of this, many businesses now use NLP and text analytics to help them get insights from their unstructured data.
Named entity extraction, an important part of NLP, lets users find important things like names, dates, currency values, and even phone numbers.
Then, the entities are put into already set-up categories. This makes it easy to find important information in documents of all sizes and formats, such as files, spreadsheets, web pages, and social text.
Even industries like insurance use NLP text analytics to help them decide how to handle claims and risks.
Natural Language Processing services are becoming increasingly popular as more organizations seek to leverage the power of NLP to improve their operations and customer experience.
Whether you are looking to develop Chabot’s, analyze customer sentiment, or translate text, NLP has the potential to help you achieve your goals.
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