Fine-grained, implicit, and anonymous

Laurianne McLaughlin comments on personalized web search in a light article in IEEE Distributed Systems:

Enhancing personalized results is a large near-term goal for Web search.

"Our challenge is to read a user's mind," says Daniel Read, vice president of product management for Ask Jeeves. It's an intriguing challenge, given that most Web searches today still contain just two to three words.

The example given of personalized search -- learning of a general interest in cooking and biasing all search results toward cooking -- is coarse-grained and doesn't capture the potential of personalization. Biasing all my searches toward a general subject interest isn't likely to work very well. How does my interest in cooking help when I'm searching for a camera? Fine-grained personalization focuses on your mission -- what you are doing right now -- and how to help you find what you want faster.

There's a brief mention of implicit vs. explicit personalization in the article. While it's true that implicit personalization is hard, working from sparse and noisy data, the article missed the major issue with explicit personalization: Most people won't do it. It takes work. People don't want more work. The entire point of personalization is to make things easier.

There's also a brief mention of privacy, something that can be handled by making users anonymous.

Personalized web, news, and blog search on Findory is fine-grained, implicit, and anonymous. We keep our eye on the goal, helping searchers find what they want quickly and easily.

[via Gary Price]