For some time, Facebook has been interested in semantic search -- using its social graph and immense amount of information about its users to deliver search results. Some have dismissed the effort, but that's premature and doesn't take into account what Facebook could do with a new hybrid: automatically curated search.
A patent granted last month to Facebook describes an approach to search that combines any type of search engine results with the popularity of each result among members of a user's social network. Although some thought the patent was on photo tags, it isn't. The implications are actually quite broad and could affect conventional search; specialty interest search topics like travel; publishing; and e-commerce; just to name a few.
The patent is called Visual tags for search results generated from social network information. Here's the simple abstract:
Search results, including sponsored links and algorithmic search results, are generated in response to a query, and are marked based on frequency of clicks on the search results by members of social network who are within a predetermined degree of separation from the member who submitted the query. The markers are visual tags and comprise either a text string or an image.In other words, Facebook would combine search results for a user with how others connected to the user in a social network responded to the same search results. If most people clicked on a handful of results, the user could see those links with some visual indication of their relative popularity. The system would work either fielding requests from third parties or for with the social network creating or obtaining the search results and delivering them to users. Here's a block diagram of the arrangement from the patent:
Although this could apply in some ways to tags on photos displayed on the web, many who looked at the patent were apparently misdirected by the term "visual tags." (I'll confess to having originally glossed over the patent myself.) But when you actually read it, what comes across is instant automatic search curation.
Some critics have largely dismissed Facebook's efforts in semantic search, assuming that what Facebook could offer would pale to the depth and breadth of Google (GOOG) or Microsoft (MSFT) actually crawling the web.
Now's the time to erase the misconception. Facebook knows that recommendations are key tools in marketing. This is the automated version of word of mouth that is supposed to sit atop search engines.
Facebook has also expanded the concept of relationship to multiple degrees of separation. Instead of your 30 or 100 or 400 connected friends, which might not be enough to get useable results, Facebook can expand the definition of the social network, much the way that LinkedIn does. If you have a couple of hundred direct connections, expanding to two degrees of separation can easily net you tens of thousands of people that are likely somewhat similar to the user in question.
Search sounds limited, but it isn't when you realize that many activities on the Web could be said to involve search and clicking a like button could be said to clicking a link. Want to buy a book? You search for a title at a reseller like Amazon (AMZN) or Barnes & Noble (BN). Want to read something? Here's a list of articles, voted by your connections, no matter what publication created the content. Want to buy something? Here are the recommended items and where you can purchase them.
The patent turns a social network and its relations into a way to augment search of any type. Given the frustrations many have with being overwhelmed by search results, Facebook has a potential huge advantage over search companies. It may also have locked down a monetarily valuable aspect of social network data that none of its direct competitors have capitalized on. This is one strategically brilliant company.
[Update: As J. Nicholas Gross pointed out on Twitter, the patent application was originally filed by Friendster. Facebook purchased Friendster's patents and patent applications last year.]
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