Máy tìm kiếm học từ người sử dụng

Tin từ PhyOrg.com

New research aims to create search-engine software that can learn from users by noticing which links they click and how they reformulate their queries when the first results don't pay off... 

Search is not a one-size-fits-all business: People searching specialized collections might use the same words in very different ways. Is "uncertainty," for example, about the location of subatomic particles, career choices, investment opportunities or romance?

"The key idea is have a search engine that gets better just by people using it," Joachims said. He and his collaborators have already created a search engine called Osmot -- the name is a play on "learning by osmosis" -- which draws on extensive research by computer scientists in machine learning. The problem the new research will address is that what the machine learns may be biased by the way it displays results.

Tôi cũng hơi ngạc nhiên vì học máy đã và đang được sử dụng rộng rãi trong các máy tìm kiếm. Tuy nhiên dự án này vẫn nhận được funding $1M từ ARRA, chứng tỏ phải có một cái gì đó rất mới và hứa hẹn. Đọc kĩ hơn thì hóa ra là cái này (theo quan điểm của tôi)

"There is a trade-off. On the one hand, you want to present the best ranking you know so far," Joachims explained. "On the other hand, the search engine has to do a bit of experimentation to be able to learn even better rankings in the long run. The key is to balance the tradeoff between presentation and experimentation in an optimal way."

This trade-off is similar to what a gambler faces in a casino and is called a "multi-armed bandit" problem. When playing a row of slot machines, each play gives you new information about how much that machine pays, but also costs you a quarter. The trick is to eliminate some machines when you're sure they won't pay off without spending more than necessary. Kleinberg's work on algorithms for solving such trade-off problems will be key to making search engines learn effectively.

Các bạn có thể xem thêm thông tin thêm ở đây
http://www.news.cornell.edu/stories/Jan10/SearchLearning.html và ở đây
http://www.cs.cornell.edu/People/tj/implicit/index.html