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Intuitive Search is a new feature coming to Google Chrome that helps you quickly find information without typing out long strings of text.

With Intuitive Search, you’ll see predictions above the URL bar based on previous searches and web pages you’ve visited.

For example, if you’re looking for “how to make money,” you might see a suggestion like “How to Make Money.” Clicking on it takes you directly to a webpage about making money. You can even add keywords to your search queries to narrow down the suggestions.

Intuitive search is one of the most exciting features that has been added to Google Chrome over the past few years. It makes finding information faster and easier than ever before.

A lot was done to improve understanding of user intent and behavior across all devices and platforms. The goal is to deliver the right answer at the right moment, no matter where the searcher is or what device he or she is using.

How does intuitive search work?

The intuitive search uses machine learning to understand what you mean when you ask a question. If you type in “pizza near me”, the system knows that you probably want to find a local pizzeria.

The system looks at the words you’ve typed and compares them against millions of other queries entered by real users. This allows the search engine to build a model that predicts which search terms are relevant to each query.

When you enter a new query, the system learns from previous queries and updates its predictions accordingly.

For example, if you previously asked for directions to a restaurant, it may predict that you’ll be asking for directions again soon. In this case, it may suggest that you use the same location name (e.g., “Pizzeria”) and include an additional word that describes the kind of food you’re interested in (e.g., “Italian").

When you click on a suggested link, the system will show you similar searches that have already been performed. You can choose to view these suggestions as a list or as cards. Cards display only the top five matches, while lists show all the matches.

The system also suggests related searches based on the keywords that you’ve used. For example, if someone types in “pizza” and “italian,” the system might suggest “pizza parlor.”

The system doesn’t just look at the words you’ve typed; it also considers the context in which they appear. For example, if a user asks for directions to a place called “Pizzeria Italiano,” the system will know that he or she probably wants to go somewhere for a pizza.

In addition to helping you find things online, intuitive search helps you find people.

When you search for a person’s name, the system will try to match your query to names associated with that person. For example, if your friend has a dog named “Max,” then searching for “max” will return a card with links to his profile and photos.

If you don’t see any results, you can refine your search by adding more specific words. For example, if Max isn’t available, typing “dog max” will narrow down the results so that you’ll see only those dogs that share his name.

You can also add a location to your search. For example, if the person you’re looking for lives in New York City, you could search for “New York City dog max.”

Intuitive search is different from predictive search because it uses machine learning to help you find things online.

Predictive search works like traditional web search engines: it looks up websites based on provided keywords. It does not learn about you over time and make personalized recommendations.

The intuitive search uses machine learning algorithms to analyze billions of data points to create models that describe how people interact with the internet. These models allow us to predict what people are going to do next. This process is called “intuition”.

In comparison, while predictive search tools work by analyzing individual words, intuitive search analyzes entire phrases and sentences. Both tools are useful when you want to find something quickly.

Intuitive search is better suited for finding information that you didn’t even know existed. And predictive search is better for finding content that you did know was out there but couldn’t remember where you saw it before.

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