[Infographic] Everything You Need To Know About Natural Language Processing In AI Search

Natural Language Processing (NLP) can be fun! Or, at least, it's pretty easy to grasp what it is about.

It might be that it all began with a question like this: "Can machines and computers understand human dialogue?"

Since the birth of computers, we have tried to "teach" them to understand languages like English. It's just another mundane task that computers can do for us so we can save our precious time.

What is Natural Language Processing?

Although our computers can work well with complex data, as long as they are structured, if not trained, machines can’t process the unstructured, multi-layered (and at many times, with many typos) everyday language of human beings.

That’s when NLP comes in.

NLP is an artificial intelligence (AI) field that focuses on enabling computers to smartly and usefully analyze, understand, and derive meaning from human language.

It involves developing algorithms and models that allow computers to process and interpret our human-language data, making it easier for us to interact with computer systems and applications.

Check out Boost’s visual explanation and summary of NLP for the basics, the latest trends in NLP, and what you can expect from the rise of NLP!

What’s next?

Today, NLP is booming as it enables computers to understand natural language better, leading to more accurate and effective communication between humans and machines.

With the ability to analyze and extract meaning from vast amounts of text and speech data, NLP has the potential to revolutionize a wide range of industries, including eCommerce site search, particularly.

Using NLP in site search engines can significantly improve the efficiency and accuracy of your site search results, especially when it comes to long-tail queries.

By implementing NLP, site search can now understand the keywords on the surface and recognize the search intent behind them, returning better keyword matching, resulting in relevant search suggestions and the likability of users purchasing from their search.