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Natural Language Processing Examples

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Natural Language Processing (NLP) deals with the use of Machine Learning (ML) to understand human languages. This advanced technology has been around for years, but people have not realized it because consumers are using this technology every day. 

NLP is a branch of artificial intelligence (AI). It performs analyzing, understanding and then generating human-like language for interfacing.

Artificial Intelligence (AI) is an advanced level of digital automation where software mimics human intelligence and judgment.

Machine Learning (ML) is a part of Artificial Intelligence (AI). ML is the ability of computers to learn by using algorithms, which are like digital flowcharts using rules.

Here are some examples of the use of Natural Language Processing (NLP) across a wide range of industries:

Social Media Monitoring

As many marketers and business owners know, having a negative review go viral on social media can destroy your brand’s reputation overnight. NLP can help with social media monitoring.

Sentiment Analysis

NLP and sentiment analysis tools are used to identify emotionally charged words that make up customer reviews. These can be used as an insight into what a specific reviewer is feeling about a brand.

Text Analysis

Text analytics can be a powerful tool for companies to organize their data and identify useful patterns and actionable insights.

Survey Analytics

Companies can also use their survey results to come up with actionable insights.

Spam Filters

Spam filters use NLP technology to analyze email subject lines and their body content. This is done by looking at various factors, such as overuse of capitalized letters, misspellings, strange or inconsistent URLs, and offers which are too easy or unbelievable, etc.

Email Classification

Gmail mines emails for keywords and phrases, then uses NLP to evaluate their content. Gmail identifies which ones are worth reading by categorizing them into categories like “social” or “business.”

Autocomplete

Google’s autocomplete feature will predict what you are interested in searching for, based on the initial few words that are typed or the characters.

Autocorrect

NLP can automatically correct your spelling errors and generate the closest possible word.

Spell Check

Spell check is a valuable tool that can help you avoid making mistakes.

Smart Search

Web pages that contain the search function can help you find exactly what you are looking for if there are relevant results.

Chatbots

Chatbots can take on several different roles, from recommending products and services to making appointments for you. They are even getting better at understanding what people want. The use of NLP with ML means that chatbots’ output has improved significantly.

Smart Home Devices

One of the most popular home technologies in recent years is Alexa. This speaker can be used to play music, control lights and other devices around your house, as well as read news headlines or weather forecasts aloud on demand. A similar device called Google Home has also been gaining more attention, thanks to its ability not only to answer questions but make reservations at restaurants. 

Conclusion

Advanced technologies employing the AI tools of NLP and ML have proven to be useful in improving the ease and efficiency of modern living everywhere. The Content Analytics Platform (CAP), developed by Scion Analytics, also uses Natural Language Processing (NLP) that can help businesses gain actionable insights with their own data analytics. 

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