It will be practically difficult to find Google Results what you need without some help sorting through the enormous amount of information available. Google’s ranking engine is designed to do just that: filter the hundreds of billions of web pages and other content in our search index in a fraction of a second to provide the most relevant, useful results.
Our computers also try to determine what type of information you want. If you used words like ‘cooking’ or ‘photos’ in your inquiry, our technologies assume that displaying recipes or images can best reflect your meaning. If you search in French, most of the results will be in that language, because that’s probably what you’re looking for. Our computers can also understand that many queries have local intent, so when you search ‘pizza’, you’ll get results about nearby pizza delivery firms.When you search for trending terms, our systems recognize that current information may be more useful than previous pages. This means that whether you’re looking for sports scores, company earnings, or anything else that’s recent, you’ll see the latest information.
In addition to keywords, our systems evaluate whether information is relevant to a query in additional ways. To determine whether search results are relevant to inquiries, we also use aggregated and anonymized interaction data. We convert that data into signals that aid our machine-learning systems in determining relevance. Consider this: when you search for ‘dogs,’ you probably don’t want a page that has the term ‘dogs’ hundreds of times. With this in mind, algorithms determine whether a page contains additional relevant information beyond the phrase ‘dogs,’ such as dog images, movies, or even a list of breeds.It is important to emphasize that, while our methods look for measurable signals to determine relevance, they are not designed to study subjective concepts such as a page’s stance or political leanings.
The web and the broader information ecosystem are always changing, and we constantly test and analyze the quality of our systems to ensure that we are maintaining the correct information relevance and authoritativeness to maintain your confidence in the results you see. Reaching the mixture.
Search also includes some elements that customize results based on your Google Account behavior. For example, if you search “events near me,” Google may tailor some recommendations to event categories we believe may be of interest to you.The purpose of these techniques is to match your interests, but not to guess sensitive traits such as your race, religion or political party.
At myaccount.google.com, you can choose which search activity is used to customize your search experience, including changing the data saved in your Google Account. Turn off Web & App Activity to disable search personalization based on account activity.In Settings, you can also find content options like Safe Search. These allow you to decide whether or not to include graphic content in search results, which may be upsetting to some people.
Key components in your Google results
To provide you with the most relevant information, search engines use various criteria and signals, such as the words in your query, the relevance and usefulness of the pages, the expertise of the sources, and your location and settings. The importance of each component varies according to the type of your inquiry. For example, freshness of content matters more when answering questions about current news topics than when answering questions about dictionary definitions.Important elements that influence which results are returned for your query:
1. The significance of your query
To generate relevant results, we first need to determine what you’re looking for – the intent of your query. To accomplish this, we use language models to try to figure out how the relatively few words you enter into the search box match the most useful content available.This includes easy steps like identifying and correcting spelling errors, as well as experimenting with our advanced synonym system, which allows us to find relevant texts even if they don’t contain the exact words you used. For example, you might have searched ‘change laptop brightness’, but the manufacturer wrote ‘adjust laptop brightness’. Because our technologies recognize the connection between words and intent, they will direct you to the appropriate content. It took five years to create this technology and improve results on more than 30% of queries in different languages.
Our computers also try to determine what type of information you want. If you used words like ‘cooking’ or ‘photos’ in your inquiry, our technologies assume that displaying recipes or images can best reflect your meaning. If you search in French, most of the results will be in that language, because that’s probably what you’re looking for. Our computers can also understand that many queries have local intent, so when you search ‘pizza’, you’ll get results about nearby pizza delivery firms.When you search for trending terms, our systems recognize that current information may be more useful than previous pages. This means that whether you’re looking for sports scores, company earnings, or anything else that’s recent, you’ll see the latest information.2. Relevance of content
The content is then analyzed by our computers to see if it contains information that is relevant to what you are looking for.When content contains keywords similar to your search query, this is the most basic indicator that it is relevant. When it comes to web sites, for example, content may be more relevant if those keywords are on the page or in headings or body of text.
In addition to keywords, our systems evaluate whether information is relevant to a query in additional ways. To determine whether search results are relevant to inquiries, we also use aggregated and anonymized interaction data. We convert that data into signals that aid our machine-learning systems in determining relevance. Consider this: when you search for ‘dogs,’ you probably don’t want a page that has the term ‘dogs’ hundreds of times. With this in mind, algorithms determine whether a page contains additional relevant information beyond the phrase ‘dogs,’ such as dog images, movies, or even a list of breeds.It is important to emphasize that, while our methods look for measurable signals to determine relevance, they are not designed to study subjective concepts such as a page’s stance or political leanings.3. Quality of content
After locating relevant information, our computers prioritize the information they find most useful. They achieve this by identifying signals that can help determine which content demonstrates experience, authority, and trustworthiness.For example, one of the many aspects we consider is whether other major websites link to or reference the content. This has often proven to be a solid indicator that the information is reliable. Feedback collected from our search quality assessment methodology is used to further optimize the way our technologies determine information quality.
The web and the broader information ecosystem are always changing, and we constantly test and analyze the quality of our systems to ensure that we are maintaining the correct information relevance and authoritativeness to maintain your confidence in the results you see. Reaching the mixture.4. Usability of web pages
Our systems also consider the usefulness of the content. All else being equal, content that people find more accessible may perform better.For example, our system will consider page experience characteristics such as whether content is mobile-friendly so that users using mobile devices can easily view it. Likewise, they check to see if content loads quickly, which is important for mobile users.
5. Context and settings
Your location, past search history, and search settings all help us ensure that your results are most useful and relevant to you at that time.We use your country and location to deliver relevant content to you. For example, if you search ‘football’ in Chicago, Google will probably show you the first results about American football and the Chicago Bears. However, in London, a search for ‘football’ returns results in relation to football and the Premier League. Search parameters, such as choosing a preferred language or SafeSearch (a technology that helps filter out obvious results), are also important indicators of which results you are likely to find beneficial.
Search also includes some elements that customize results based on your Google Account behavior. For example, if you search “events near me,” Google may tailor some recommendations to event categories we believe may be of interest to you.The purpose of these techniques is to match your interests, but not to guess sensitive traits such as your race, religion or political party.
At myaccount.google.com, you can choose which search activity is used to customize your search experience, including changing the data saved in your Google Account. Turn off Web & App Activity to disable search personalization based on account activity.In Settings, you can also find content options like Safe Search. These allow you to decide whether or not to include graphic content in search results, which may be upsetting to some people.
