You want the answer, not trillions of webpages. Algorithms are computer programs that look for clues to give you back exactly what you want.
For a typical query, there are thousands, if not millions, of webpages with helpful information. Algorithms are the computer processes and formulas that take your questions and turn them into answers. Today Google’s algorithms rely on more than 200 unique signals or “clues” that make it possible to guess what you might really be looking for. These signals include things like the terms on websites, the freshness of content, your region and PageRank.
There are many components to the search process and the results page, and we’re constantly updating our technologies and systems to deliver better results. Many of these changes involve exciting new innovations, such as the Knowledge Graph or Google Instant. There are other important systems that we constantly tune and refine. This list of projects provides a glimpse into the many different aspects of search.
Displays immediate answers and information for things such as the weather, sports scores and quick facts.
Predicts what you might be searching for. This includes understanding terms with more than one meaning.
Finds results out of millions of books, including previews and text, from libraries and publishers worldwide.
Shows the latest news and information. This includes gathering timely results when you’re searching specific dates.
Displays immediate results as you type.
Shows you image-based results with thumbnails so you can decide which page to visit from just a glance.
Uses systems for collecting and storing documents on the web.
Provides results based on a database of real world people, places, things, and the connections between them.
Includes improvements designed specifically for mobile devices, such as tablets and smartphones.
Includes results from online newspapers and blogs from around the world.
Gets to the deeper meaning of the words you type.
Provides features like “Advanced Search,” related searches, and other search tools, all of which help you fine-tune your search.
Reduces the amount of adult web pages, images, and videos in your results.
Creates new ways to search, including “search by image” and “voice search.”
Uses a set of signals to determine how trustworthy, reputable, or authoritative a source is. (One of these signals is PageRank, one of Google’s first algorithms, which looks at links between pages to determine their relevance.)
Shows small previews of information, such as a page’s title and short descriptive text, about each search result.
Identifies and corrects possible spelling errors and provides alternatives.
Recognizes words with similar meanings.
Tailors results based on your language and country.
Blends relevant content, such as images, news, maps, videos, and your personal content, into a single unified search results page.
Provides more relevant results based on geographic region, Web History, and other factors.
Shows video-based results with thumbnails so you can quickly decide which video to watch.
Our goal is to get you to the answer you're looking for faster, creating a nearly seamless connection between you and the knowledge you seek. If you’re looking to deepen your understanding of how search has evolved, this video highlights some important features like universal results and quick answers.
A typical algorithmic change begins as an idea from one of our engineers about how to improve search. We take a data-driven approach and all proposed algorithm changes undergo extensive quality evaluation before release.
Engineers typically start by running a series of experiments, tweaking small variables and getting feedback from colleagues until they are satisfied and ready to release the experiment to a larger audience.
This document is a version of our Search Quality Rater Guidelines, which gives evaluators examples and guidelines for appropriate ratings. The document focuses on a type of rating task called “URL rating.” In this kind of task, the evaluator looks at a search query and a result that could be returned. They rate the relevance of the result for that query on a scale described within the document. Sounds simple, right? As you can see, there are many tricky cases to think through.
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The first phase is to get feedback from evaluators, people who evaluate search quality based on our guidelines. We show evaluators search results and ask them to rate the usefulness of the results for a given search. Note: These ratings don’t directly impact ranking.
In a side-by-side experiment, we show evaluators two different sets of search results: one from the old algorithm and one from the new, and we ask them for details about which results they prefer.
If the evaluators’ feedback looks good, we move forward with a “live traffic experiment.” In these experiments, we change search for a small percentage of real Google users and see how it changes the way they interact with the results. We carefully analyze the results to understand whether the change is an improvement to the search results. For example, do searchers click the new first result more often? If so, that’s generally a good sign.
Finally, our most experienced search engineers carefully review the data from all the different experiments and decide if the change is approved to launch. It sounds like a lot, but the process is well refined, so an engineer can go from idea to live on Google for a percentage of users in 24 hours. Based on all of this experimentation, evaluation and analysis, we launched 665 improvements to search in 2012.
Data from 2012
