How to use Natural Language Processing in Mobile App?
In today’s technologically advanced world, the usage of mobile devices is increasing by each passing day. With this rapid growth in mobile devices' usage, more and more mobile app content offers an opportunity for mining useful information.
In today’s technologically advanced world, the usage of mobile devices is increasing by each passing day. With this rapid growth in mobile devices' usage, more and more mobile app content offers an opportunity for mining useful information.
Everything today is all about text and voice data. It can be a news feed, social media messages, the free-text format in web pages, and emails. To derive meaning from these data, many systems have come up with additional functions with our language. These systems are based on Natural Language Processing (NLP), combining computational linguistics and AI. The best examples of NLP are Siri from Apple, Cortana from Microsoft, and Ok, Google from Google. This specifies the ability of NLP-based mobile devices to understand the human language.
Natural Language Processing is a technology that helps in making the mobile app smarter by automatically analyzing the meaning of the content and taking the appropriate action on behalf of mobile users. In this blog, let's understand everything about Natural Language Processing, the technology for mobile app development using Machine Learning, and how it can be used in mobile apps.
What is Natural Language Processing?
Natural Language Processing (NLP) is an automatic manipulation of a natural language like text and speech by software. It is a technology used to aid computers or mobile devices to understand the human language.
NLP's objective is to read, decipher, and make sense of the human language in a valuable manner. The majority of the NLP techniques rely on Machine Learning (ML) to derive meaning from human words.
What is Natural Language Processing Used For?
- NLP is used in language translation applications such as Google Translate.
- Personal assistant apps like Siri, Cortana, Alexa, and Ok Google use NLP.
- Interactive Voice Response apps used in call centers. It can respond to individual users’ requests.
How Does Natural Language Processing Work?
NLP applies algorithms to identity and extracts natural language rules in such a way that the unstructured language data is converted into understandable computer language.
Once the text is provided, the computer utilizes algorithms to extract its meaning and collect the essential data from them.
Natural Language Programming in Mobile Apps
NLP is a technology that is advanced beyond virtual assistants. Mobile app developers are integrating NLP to make mobile app devices more accessible to individuals with physical disabilities.
Businesses come with advanced solutions for mobile app development using Machine Learning and NLL. These solutions enable users to ask any questions using normal language and receive an answer in the same way. Let’s see various types of mobile applications that use NLP technology in different sectors.
1. Use of NLP to Drive an Information Engine
According to researchers, Google will soon adapt to NLP-based technology in mobile devices to provide better results. Besides this, currently, virtual assistants are the best at providing a basic answer to a simple question. In some time, it will start in-depth explanations to the user’s complicated questions.
NLP has tremendous potential when it comes to creating and pulling information from stores. For instance, an information engine that uses websites, videos, ebooks, data stores, videos, and television footage with up-to-the-millisecond accuracy. This type of invention can revolutionize the way people absorb and utilize information.
2. Use of NLP for Fighting Spams
People face an issue with a lot of spam messages coming every day in their inbox. NLP can be a useful technology when it comes to monitoring the spam messages. It is a technology that reads and hears the messages. This capability of NLP technology can read the content of blog comments, email messages, private messages on social media platforms, and more. Then the content is compared to known spam messages to identify the spam. This application of natural language processing is growing in mobile apps that have the potential for spam issues.
3. Use of NLP for Mobile Apps in Medical Field
NLP is commonly used in the medical sector, especially when it comes to apps for wearable health equipment. NLP also supports apps that allow you to use verbal input in place of typing. Below are the applications for NLP in the healthcare sector-
Verbal Updates & Input: Physicians and nurses can use NLP technology to automatically fill out a health history form of patients by only using an app while talking to patients. Similarly, a surgeon can verbally state findings while conducting a surgical procedure. This type of mobile app can also be used to send health updates to the family of the patients.
Note-taking: NLP technology can help patients take notes derived directly from the doctor’s speech. This type of apps can provide patients with a useful record of medication names, dosage information, and other tips.
Conclusion
Natural language processing is a technology that can have a remarkable impact on the world of mobile app development. NLP supports various apps and virtual assistants that can make mobile devices smarter than before. In this article, we saw how NLP works and how it affects mobile apps.
