Natural language processing 101

With buzzwords like AI and machine learning being thrown around more than a football at training camp, it’s important for marketers to understand the ins and outs of how the various components that make up these technology advances work.

Advancements in natural language processing( NLP) were one of the major steps forward that allowed AI to become mainstream. According to everyoneas favorite resource, Wikipedia, NLP is aa field of computer science, artificial intelligence and computational logistics concerned with the interactions between computers and human languages.a

In laymanas terms, NLP permits computers to understand what we are telling them.

As computers have become more powerful — increasing their ability to attain mass amounts of computations analyzing inputs and learning how we “speak” to them — their ability to understand us has significantly improved. This is due to business assuring NLP, and ultimately, AI, as a business possibility. Companies such as IBM have invested a large amount of capital into programs like Watson that utilize NLP.

How and where NLP is being used

Social listening :

One of the areas that has utilized NLP for the last few years has been social listening tools. If you’ve ever operate a social listening report and analyzed sentiment, this is a very basic example of NLP. The tools analyze the content within tweets, Facebook status updates and YouTube comments and determine if the shares were positive, negative or neutral. Basic NLP processing would highlight certain terms like “hate” or “sucks” as negative and terms like “awesome” and “love” as positive.

Many tools used a economically more advanced approach, being able to differentiate between the following 😛 TAGEND ” I got sick on the plane ride home .” A ” I had so much fun — the roller coaster was sick !”

By looking at context and the other terms used within the statement, social listening tools are able to differentiate between the two uses of “sick” and segment them into positive or negative shares. Many social listening tools have advanced this even further, segmenting shares to classes like rage, happiness, allegiance and other emotions.

As NLP has improved, so has the capacities for social listening tools to understand what we share on social media.

Chatbots :

Chatbots would not be here without NLP. By being able to comprehend your input, they can provide you with a quick answer that fulfills your petition. Advancements in NLP have helped chatbots understand shorthand and misspellings to acknowledge the context behind your inputs.

This can be something as simple as a chatbot understanding that “ty” means” Thank You” and is not a misspelling of the word “tie.”

Search algorithms :

One of the most fascinating uses of NLP is Googleas RankBrain algorithm. As it constantly learns and evolves to provide better search results, NLP is utilized to understand the context behind your searches.

[ Read the full article on MarTech Today .]

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