To do this, NLP software uses machine learning and artificial intelligence technologies.
The main goal of natural language processing is for computers to achieve advanced text comprehension at a level of understanding similar to that of humans. Why?
When computer systems reach this level, they can:
Natural language processing will give your company the ability to quickly develop while making full use of your data. NLP solutions provide the necessary tools to analyze both numerical and linguistic data.
Discover the NLP solutions that best suit your business needs.
Natural Language Processing systems are usually based on machine learning algorithms
Rather than manually coding large sets of rules, NLP can rely on machine learning to learn these rules automatically by analyzing a set of examples and drawing statistical conclusions.
Learn more about NLP algorithms.
At Addepto, we believe that continual improvement, not staying in the same place, is key. Advanced technologies offer many solutions for development.
Our team consists of experts in the field of NLP, data science, AI and machine learning. We have experience in working on NLP solutions for international companies.
Get in touch with our experts to find out more about our services and decide if we fit your business.
NLP can provide manufacturers with greater visibility into the areas of their supply chain that are lagging behind.
Some of the most popular NLP solutions in the manufacturing industry include:
The most popular NLP solutions in the financial sector include:
Their customer data can be analyzed and, based on conclusions, used to improve the quality of service and customer loyalty.
The most effective NLP solutions include:
Addepto impressed us with the knowledge of the latest technological trends and enthusiasm for working on ambitious projects. They took into account our needs and suggestions and made every effort to create solutions tailored to our expectations.
NLP solutions such as autocorrect and autocomplete analyze personal language patterns and determine the most appropriate suggestions for individual users.
Virtual smart assistants, such as easily recognizable Siri or Alexa, use NLP technology to understand human inquiries and respond to their needs.
Search engines use NLP to better understand what users are looking for and be able to find relevant information faster.
Text classification is critical to automating the understanding, processing, and categorization of unstructured text. NLP models allow you to organize data using predetermined tags.
Natural language processing is able to automatically identify specific keywords, product names, descriptions, etc. within text.
NLP can quickly extract crucial information from the text and summarize it based on key phrases from text or determined inferences.
Apple
Siri, Apple’s smart assistant, uses NLP to help it recognize speech patterns and understand contextual cues.
Thanks to natural language processing, intelligent assistants like Siri can improve our daily life by making things like ordering specific products faster and easier.
Customers have noticed the benefits of this NLP solution, and in the US alone, Siri has approximately 375 million active users every month!
Increasingly, devices of everyday use such as light switches, cars, food processors, etc. implement solutions based on NLP technology. This trend will only increase in the future.
“We are entering a new world. The technologies of machine learning, speech recognition, and natural language understanding are reaching a nexus of capability. The end result is that we’ll soon have artificially intelligent assistants to help us in every aspect of our lives.” – Amy Stapleton, Analyst, Opus Research
Amazon
Companies like Amazon are aware of the business opportunities that come with natural language processing.
Amazon Comprehend uses NLP solutions to extract information from text documents.
This technology provides insight by recognizing language, titles, key phrases, and many other basic elements of text documents.
Another company that uses NLP solutions to improve its services is Google. Its app, Google Translate, uses natural language processing technology to offer high-quality translation services worldwide.
Google Translate is used by 500 million people every day, so they can understand over 100 different languages.
Such NLP applications improve communication between people from different countries and break down language barriers. It enables individuals to understand foreign documents, catalogs and even technical manuals.
Google’s strengths in areas like search, geographical information, image recognition and natural language processing, make its potential for assistive technologies enormous.
“I think we’re at the forefront of that development, we’re pushing hard and getting there.” – Sundar Pichai, Google CEO
NLP is used for language analysis both in text and speech. NLP solutions assist humans in everyday activities like understanding foreign languages, emailing, and text categorization.
NLP enables computers to perform language-related tasks and interact with humans.
The most effective NLP solutions include:
Some of the most popular NLP tools are:
AI (Artificial Intelligence) is a wide field of studies that focuses on how machines can understand our world. NLP is just a branch of AI, focusing on understanding human language.
We can distinguish five phases of NLP:
The main goal of natural language processing is to achieve a human-like level of language processing. It should be able to make sense of the text and perform text classification, translation, etc.
NLP is facing challenges in understanding and modeling different elements in variable contexts.