By Sean P. Aune
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It’s that time of year again for the major search engines to release their top search queries of the year. Yahoo traditionally goes first, and today’s the day. And once again, people can’t seem to help but type “Britney Spears” into every search box they come across.
The top queries of the year on Yahoo are:
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Six Apart has sold its hosting blogging platform LiveJournal, which it acquired in January 2005, to Moscow-headquarted SUP (pronounced “soup”), the company said this evening. Terms of the deal were not disclosed. SUP previously acquired licensing rights in October 2006 permitting them to manage LiveJournal in Russia, where the platform dominates blogging culture.
“This allows Six Apart to focus on their remaining three brands (Vox, TypePad and MoveableType)” CEO Chris Alden told me this evening. LiveJournal, created by Brad Fitzpatrick in 1999, was the lone service not built in house. “We have very ambitious plans for our remaining brands going forward” he added.
Since the 2005 acquisition, Live Journal has grown from 5 million to over 14 million accounts. But overall unique visitor and page view growth has been static for the last year. In October 2007 Comscore says LiveJournal had 13.8 million worldwide unique visitors generating 475 million page views. That’s up only slightly from the 11.1 million visitors and and 408 million page view per month a year ago.
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Google continues to make forays into the world of images, on several different fronts.
Image recognition in Google searches is taking shape. Although not highly publicized yet, there is a way to search images for certain elements such as faces. For example, if you do an image search for “USA”, you get a slew of maps. If you do the search “usa imgtype=face”, the search does indeed turn up pictures of people.
According to Google’s Sergey Brin, it will be possible for the computer to soon automatically search images for patterns, such as that of an elephant, in a picture.
While identification of physical objects in pictures will go a long way towards helping categorize the trillions of images on the web, there are aspects of classification which are abstract, and subjective. For example, the picture on the left can be categorized as 1. sky, 2. bird or 3. soaring.
A new Google project called Google Image Labeler has popped up for improving the relevance of image search. At any particular time, two random users who have signed up for the experiment, are paired up. Over a period of 2 minutes, both are shown a set of images for which each provides as many labels as they can think of. When the pair has a match, each of them get a certain number of points depending upon how specific the description is.
I tried out the application in guest mode (see the pictures below). Interestingly, each picture starts out with a list of “off-limit” terms which are actually the first ones that would come to mind. The purpose of these might be to look beyond the most obvious categorization. For example, in the map example below, the descriptions “map” or “Australia” were off limits.
While the Image labeler seems like a pretty entertaining project at this point, Google’s objective is to probably use the real human fuzzy network data to refine its automatic image filtering, rather than a simple grand scheme to use free cpus to classify all of the web’s pictures.
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