A new game asks users to help refine search results.
By Will Knight
Microsoft's labs in Redmond, WA, have released an online game to help fine-tune search results.
the game presents
players with web pages and asks them to guess the queries that would
produce the page within its first five results. Players score 100
points if the page is no.1 on the list, 90 points if it's no.2, and so
on. Bonuses are also awarded for avoiding frequently-used queries.
The idea is to gather useful information on user search habits which
could be used to fine tune search algorithms and ranking scheme. The
game was developed
by Chris Quirk and Raman Chandrasekar at Microsoft,
and colleagues from Georgia Tech and the Chinese University of Hong
Kong, and it was unveiled this week at the SIGIR09 conference in Boston.
Page Hunt is a clever twist on "human computation"--using people to perform tasks that computers find difficult to do. Luis von Ahn, a professor at Carnegie Mellon University,
has been a pioneer in this area, and has developed several similar projects: spam-fighting
text puzzles that simultaneously help
digitize old books, and games that help tag images
and music with the relevant keywords. Another cool example of human
computation in action is, of course, Amazon's
The researchers behind
Page Hunt have already made one curious finding while testing the game
internally: the longer a page's URL (in characters), the
harder it was for users to match the page to query words. The research
don't speculate about why this should be, but here's a graph showing
the relationship between URL length and the "findability" of a page:
I found Page Hunt
strangely addictive, although my first score was a pathetic 630.
A paper describing
the Page Hunt research can be found here (pdf).