Applications of NLP in Artificial Intelligence
Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) that studies how machines understand human language. Its goal is to build systems that can make sense of the text and perform tasks like translation, grammar checking, or topic classification.
- Email Filters:
Email filters are one of the most basic applications of NLP online. It started with spam filters, one of the more prevalent, newer applications of NLP is found in Gmail’s email classification. The system recognizes if emails belong in one of three categories (primary, social, or promotions) based on their contents. This keeps your inbox to a manageable size with important, relevant emails you wish to review and respond to quickly for all Gmail users.
2. Smart assistants
Smart assistants like Apple’s Siri and Amazon’s Alexa recognize patterns in speech.
We’ve become used to the fact that we can say “Hey Siri”, and ask a question, and she understands what we said and responds with relevant answers based on context.
3. Search results
Search engines use NLP to surface relevant results based on similar search behaviors or user intent so the average person finds what they need without being a search-term wizard.
4. Predictive text
Things like autocorrect, autocomplete, and predictive text are so commonplace on our smartphones. Autocomplete and predictive text are similar to search engines in that they predict things to say based on what you type, finishing the word, or suggesting a relevant one.
5. Language translation
NLP online translator can translate the language from one to another more accurately and present grammatically correct results.
6. Text analytics
Text analytics converts unstructured text data into meaningful data for analysis using different linguistic, statistical, and machine learning techniques.
7. Data analysis
Natural language capabilities are being integrated into analysis workflows as more BI vendors offer a natural language interface to data visualizations.
8. Digital phone calls
Automated systems direct customer calls to a service representative or online chatbots, which respond to customer requests with helpful information. This is an NLP practice that many companies, including large telecommunications providers have put to use.
9. Social media monitoring
Various NLP techniques are used by companies to analyze social media posts and know that what customers think about their products. Companies are also using social media monitoring to understand the issues and problems that their customers are facing by using their products.
10. Targeted Advertising
Targeted advertising works mainly on keyword matching. The Ads are associated with a keyword or phrase, and it is shown to only those users who search for the keyword similar to the keyword with which the advertisement was associated.
11. Hiring and Recruitment
In a company in Hiring and Recruitment process HR have to go through by hundreds or thousands of resume for shortlisting resumes for interview. manually doing all this will take lots of time and effort but with the help of NLP, recruiters can find the right candidate with much ease. This simply means that the recruiter would not have to go through every resume and filter the right candidates manually. The technique, like information extraction with named entity recognition, can be used to extract information such as skills, name, location, and education.
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