Image Labeler: Lazy Google or Smart Google?

17 10 2008

Google are great at indexing information. It is what makes them the world’s #1 search engine with over 80% market share in the UK. They are the first stop for information, amongst other things, images.

Google has nailed indexing websites that a brimming with text, but indexing images is a damn sight harder. Lets break this down…

Google has (a probably average) of at least 100 words to index on a webpage. This gives Google clues about the pages subject. With an image it has only one piece of text: the file name. This is not enough for Google thoroughly index an image, thus making Image Search a poor sibling of Google’s uber site search.

If images were able to be tagged, like blog posts, with what they contain then it would be massivley simpler to index them. But there are millions, if not billions, of images that would need tagging, thats way too much work.

Google have found a way round this: get users to tag images for them!

Its not easy getting people to do your work for you for free, but Google had another brainwave: turn it into a game!

And from that, Google Image Labeler was born:

Over a two-minute period, you and your partner will:

  • View the same set of images.
  • Provide as many labels as possible to describe each image you see.
  • Receive points when your label matches your partner’s label. The number of points will depend on how specific your label is.
  • See more images until time runs out.

After time expires, you can explore the images you’ve seen and the websites where those images were found. And we’ll show you the points you’ve earned throughout the session.

Google are not lazy. They have just been amazingly clever.

Do you think Google’s Image Labeler game is a great move or just exploitation of bored, Internet users? Let us know, leave a comment!

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3 11 2008
Google Learns To Read Text From Images! « Just Google It

[…] Google It. Their textual search results are unrivalled. Their image search is, day-after-day, being improved by human interaction through the Image Labeler game. But it was rough-going when they tried to index both at the same time: Text on […]

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