I think it was supposed to cluster users who often voted the same way, and then infer that if a user voted up an article, most people in the same cluster as that user would also like the article.
I wonder why it didn't work. They certainly have enough of a dataset to play with by now. I wonder if it's computationally too intensive to continually update each user's results, or too difficult to come up with a good algorithm.
Does this "recommended page" problem bear any resemblance to the Netflix prize problem?
Creating a good recommended page would certainly lure me back to reddit.
I don't think the founders have much of an incentive to change reddit a whole lot. Also, the existing algorithm is definitely computationally intensive: it takes 12 seconds to generate a new recommended page.
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I think it was supposed to cluster users who often voted the same way, and then infer that if a user voted up an article, most people in the same cluster as that user would also like the article.
It never worked for me unfortunately.
It never worked for me unfortunately.
Me neither.
I wonder why it didn't work. They certainly have enough of a dataset to play with by now. I wonder if it's computationally too intensive to continually update each user's results, or too difficult to come up with a good algorithm.
Does this "recommended page" problem bear any resemblance to the Netflix prize problem?
Creating a good recommended page would certainly lure me back to reddit.
I don't think the founders have much of an incentive to change reddit a whole lot. Also, the existing algorithm is definitely computationally intensive: it takes 12 seconds to generate a new recommended page.
That would be a better strategy if they advertised it well. It would give users a strong incentive to vote on articles.