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Search Engine Learns From User Feedback
An anonymous reader writes "Ian Clarke, founder of the Freenet project, has set up a web search engine that allows users to rate each of the search results it returns. WhittleBit will use your feedback to determine which keywords should be added or removed from your search, then you can search again to get more accurate results. This could be useful for those cases where Google just refuses to return the search results you want. Could improved interactivity be the next big search engine advancement after Pagerank?"
Great idea until the second month when your local viagra spammer's SEO guy moves all his pages to the top of the search for "Futurama" or "Ninja Turtles."
who wants to wade through results and rank them? I came here to search!
That's why google is king. It doesn't require you to do *anything*. It barely *allows* you to do anything.
And it still returns what you need.
That's the perfect UI.
Perhaps one reason there were so few result returned is the fact that this seems to be more of a proof of concept than a fully functioning engine. Imagine combining a feedback mechanism with an already excellent search like Google. This can't stand alone, but it would be an excellent addition to an engine that already has a huge index.
One thing that does worry me, what about the potential for abuse. Something like a script that connects to whittlebit, searches by a keyword important to your industry, and gives all of your competitors links thumbs-down.
Where's my lobbyist? Right here.
You're missing the point. The system isn't watching user actions while searching to fine tune OTHER user's results, but to fine tune THAT user's results.
While you can certainly claim that one user's actions MIGHT indicate relevance for another user's queries, it's certainly true that if a user gives you a clue that the document you have returned is irrelevant, it must be irrelevant.