That’s fair. I guess if you will allow me to re-state my idea with your ideas in mind:
Aggregate rating systems are best. But occasionally they are wrong. Sometimes I will see a movie has a high rotten tomatoes score but I still hated it. I don’t watch a lot of movies so this happens often actually. Having someone similar to me, who is watching highly rated movies can usually save me time by predicting whether I will like something or not.
You are right aggregate is best. But I think having an aligned friend who knows your preferences can help build on top of that. Or rather help me filter.
I’m my original post I failed to realize that my brother and I are both watching movies that are highly rated. I think using both in conjunction works great. So I’m not disagreeing with you, rather building off your thoughts.
But to pose an interesting question. If tomorrow, rotten tomatoes had an option to find a user who EXACTLY matched the ratings you gave. For instance both of you gave Titanic a 7, Forest Gump a 8, etc. Then the algorithm tells you this user that most matches you, watched Shrek 6 yesterday and gave it a 10⁄10. Would you prefer that algorithms suggestion over just an aggregate average rating?
There are a lot of cool algorithms that could be applied to this, even a neural net that could take your past ratings and “predict” movies you would like next. I’m sure one might be more accurate than averaging method. SVN or KNN algorithms seem promising off the top of my head.
That’s fair. I guess if you will allow me to re-state my idea with your ideas in mind:
Aggregate rating systems are best. But occasionally they are wrong. Sometimes I will see a movie has a high rotten tomatoes score but I still hated it. I don’t watch a lot of movies so this happens often actually. Having someone similar to me, who is watching highly rated movies can usually save me time by predicting whether I will like something or not.
You are right aggregate is best. But I think having an aligned friend who knows your preferences can help build on top of that. Or rather help me filter.
I’m my original post I failed to realize that my brother and I are both watching movies that are highly rated. I think using both in conjunction works great. So I’m not disagreeing with you, rather building off your thoughts.
But to pose an interesting question. If tomorrow, rotten tomatoes had an option to find a user who EXACTLY matched the ratings you gave. For instance both of you gave Titanic a 7, Forest Gump a 8, etc. Then the algorithm tells you this user that most matches you, watched Shrek 6 yesterday and gave it a 10⁄10. Would you prefer that algorithms suggestion over just an aggregate average rating?
There are a lot of cool algorithms that could be applied to this, even a neural net that could take your past ratings and “predict” movies you would like next. I’m sure one might be more accurate than averaging method. SVN or KNN algorithms seem promising off the top of my head.