5 ms·
1) Space for algorithmic innovation? (which is the coolest thing to be in front of but I guess there must be already some algorithm application to handle this c
by jacabado 16y ago
1) Space for algorithmic innovation? (which is the coolest thing to be in front of but I guess there must be already some algorithm application to handle this case)
2) Why? Could you give some examples? I ask because I also think that rating-less like is dependent on the subjects personality. For me a dislike button should be much more meaningful because as a optimistic there is a bigger range of things I like with a bigger variation of likeness, while when I (would) hit dislike I must be pretty sure that I don't like it.
3) I agree but the implication is that sites should use negative qualifications differently, it shouldn't be shared with others in the same way the likeness is shared unless, as in your suggestions, they enable you to find better content. I don't go telling people I dislike that I dislike them, I just avoid them. The approach should be similar.
- nkurz 16y agoPersonally, I think there is a lot of room for algorithmic improvement on recommendations. Most of the existing systems are really prediction algorithms, which have been shoe-horned into making recommendations. I think this is primarily because accuracy of prediction is easier to measure (RMSE) than accuracy of recommendation, and the academic papers need something they can measure. I agree that inferring 'like' is also difficult, and definitely prefer explicit rating systems. But for a site like Amazon, it's often a reasonable presumption that a user who buys an item likes it. But inferring that they dislike all the items they don't purchase is much less reasonable. Same for viewing webpages, or listening to music, or renting movies. If you want to be sure of a 'dislike', it probably will require action from the user.