What is the Difference between Semantic and Google Search?

It might be hard to believe, but less than 35 years ago search engines simply did not exist. It was only 30 years ago that Yahoo brought the power of search engines into our homes, changing the way we look for information forever.

Google is now synonymous with the term search engine, but it was only 26 years ago that the soon-to-be tech giant broke new digital ground when it found a way to make search engines profitable.

These search engines work by matching words. They are text-based search engines. That is, they take the keywords or phrases inputted by the users and look for matches for them across the internet.

Now, the way we use the internet is set to change again with the rise of semantic search.

In fact, the history of semantic search is longer than you might think. The idea of search systems based on what the user means rather than what the user types was being discussed in 1999.

Since then, a series of technological breakthroughs have brought us closer and closer to realizing this game changer, from the development of ontologies and knowledge graphs to the arrival of AI.

Now, the internet is about to change forever. Again.

What’s Google Search?

Google Search is primarily lexical. That means it works by matching the keywords you enter with websites that mention them.

Initially this was literal, looking for pages where the words you type in appear. It’s since become a little more sophisticated and understands synonyms, typos, and looks at parts of a webpage not everyone sees like the metadata.

Google now even includes natural language processing, so you can seemingly ask it questions. Ultimately though, it’s still matching words you input with words on a webpage.

What’s semantic search?

Semantic Search is, well, semantic. That means it works by matching the meaning of your query with results that provide answers.

To do this, semantic search leverages the rapidly increasing power of AI and machine learning, along with accelerating data processing capabilities. It considers the user’s own previous search behavior, general users’ search behavior, and the query’s conceptual proximity to other queries.

Semantic search tries to understand the users’ intent, treating each search as a question to be answered rather than a set of values to be matched.

Why does it matter?

This should matter to everyone. We’d all like to have search results that give us the results we want!

However, many industries will be revolutionized by semantic search. The way we search for some industries is already changing.

Think about searching for a restaurant’s name. Once upon a time, this would’ve yielded a bunch of websites where the restaurant’s name is mentioned. Hopefully the restaurant’s own site would rank first, where you can check out the menu, find out how to get there, and make a reservation.

If you wanted to see some honest reviews, you might need to scroll a little further down the list of results.

With semantic search, the search engine already has an idea of why you’re searching the restaurant’s name. Because you want to eat there! For that you need to know where it is, if it’s any good, and how to get a table.

So it includes maps, ratings and contact details in the search results to make all this easier for you. It’s answered your question without you even having to ask it.

Convenient right? But this could be an even bigger game changer for industries like healthcare.

Being able to effectively match symptoms to a condition is vital for quick and effective diagnosis. But describing symptoms can be tricky.

If we were with our doctor we could point, use facial expressions, and rely on other means of communication that go beyond words. We can’t do this when we’re searching a database if that search is only able to match words with results.

But imagine if it could understand what we’re asking?

The ability to search a database for answers rather than matches won’t just change the way we use the internet, but our approach to data in general.