This Is How Google Autocomplete Predictions Works In Search
San Francisco: As soon as you start typing on Google Search, predictions appear in the search box to help you finish what you’re typing and the credit goes to the Autocomplete feature.
According to Google, predictions reflect searches that have been done on Google.
“To determine what predictions to show, our systems begin by looking at common and trending queries that match what someone starts to enter into the search box,” the company explained in a blog post.
For instance, if you were to type in “best star trek”, we’d look for the common completions that would follow, such as “best star trek series” or “best star trek episodes.”
“We don’t just show the most common predictions overall. We also consider things like the language of the searcher or where they are searching from, because these make predictions far more relevant,” Google said.
To provide better predictions for long queries, Google systems may automatically shift from predicting an entire search to portions of a search.
The company said it also takes freshness into account when displaying predictions.
“If our automated systems detect there’s rising interest in a topic, they might show a trending prediction even if it isn’t typically the most common of all related predictions that we know about”.
Predictions also will vary depending on the specific topic that someone is searching for.
People, places and things all have different attributes that people are interested in.
For example, someone searching for “trip to New York” might see a prediction of “trip to New York for Christmas,” as that’s a popular time to visit that city.
“Predictions will reflect the queries that are unique and relevant to a particular topic,” Google said.
Autocomplete differs from Google Trends which is a tool for journalists and anyone else who’s interested to research the popularity of searches and search topics over time.
Google said that predictions aren’t perfect and it has systems designed to prevent potentially unhelpful and policy-violating predictions from appearing.
“Secondly, if our automated systems don’t catch predictions that violate our policies, we have enforcement teams that remove predictions in accordance with those policies,” the tech giant explained.