Have you noticed that you don't always get the exact terms you searched for anymore on Google? Instead of oh-so-literal keyword matching and filters such as +site:valleywag.com, Google lines up a team of technologies that try to guess what you're really looking for. Information retrieval specialist Amit Singhal walked through them in a Google Blog post . I edited out 80 percent of the verbiage — mostly by deleting the term world class every time it popped up — and left in the technical parts.
* Understanding pages: One of the key technologies we have developed to understand pages is associating important concepts to a page even when they are not obvious on the page. A user searching for [cool tech pc vancouver, wa] finds the homepage www.cooltechpc.com even though the page does not mention anywhere that they are in Vancouver, WA.
* Understanding queries: We have a spelling suggestion system, a synonyms system, and a concept analysis system. For example, our algorithms understand that in the query [new york times square church] the user is looking for the well-known church in Times Square and not for articles from the New York Times.
* Understanding users: This work starts with a localization system, and adds to it personalization technology, and several other features. Universal Search. A user looking for [bank] in the US should get American banks, whereas a user in the UK is either looking for the Bank Fashion line or for British financial institutions. The same query can mean entirely different things in different countries. For example, [Côte d'Or] is a geographic region in France - but it is a large chocolate manufacturer in neighboring French-speaking Belgium.
Another case of user intent can be observed for the query [chevrolet magnum]. Magnum is actually made by Dodge and not Chevrolet. So we present the results for Dodge Magnum with the prompt See results for: dodge magnum in our result set.
Universal Search is another example of how we interpret user intent to give them what they (sometimes) really want. Someone searching for [bangalore] not only gets the important web pages, they also get a map, a video showing street life, traffic, etc., and at the time of writing there is relevant news and relevant blogs about Bangalore.
Cross Language Information Retrieval (CLIR) allows users to first discover information that is not in their language, and then using Google's translation technology, we make this information accessible. I call this advance: give me what I want in any language. A user searching for Disney movie songs in Egypt with the query [أغاني أفلام ديزني] is prompted to search the English web.