Where does it get your move list from? I know I rated a lot of movies on my rotten-tomatoes profile, can this be used?
EDIT: Also, it's not clear that you can start using the product without Facebook, I like the fact that it lets you rate a couple movies before asking you to sign-up (with Facebook or with a regular email/password)
Did this work for anyone? Meaning; anyone got good (for them) suggestions? Where does the data set come from?
Am I blind or did I miss the button for 'I did not see this movie'? Because I didn't see quite a lot of the ones that I was asked my opinion on.
All in all, I always like these kind of things, but asking me if I like that Star Wars drivel 3 times in a row and then asking me if I liked 4 movies I never saw skewed my results a bit I think.
Keep improving though! If I can get only one 'wow' movie I never saw recommended, I would be really happy.
I'm impressed. It gave me what I thought to be a small, weak data set, but the recommendations were better than those I get from Netflix, which has much, much more of my data to work with.
Same here. It showed me a bunch of blockbusters that I either haven't seen, were just kinda good, or even meh.
And came up with amazing recommendations of really cool movies I've either watched and loved, or haven't seen but always wanted to. Even the top pick for "movies from this year" was the one movie where I saw a trailer and said WANT.
What makes the rankings better than you get from Netflix? I'm impressed that it managed to suggest Clue to me, but I haven't seen the rest, so can't really say if I would like them. (More, if it just suggests movies I've already seen and liked... hard to say it did a good job, or that I'm just predictable in cliques of movies. :) )
The point of this site is to give you recommendations you haven't seen. I hate it when all the recommended movies on Netflix are all movies I've seen and can't get rid off...
These recommendations are pretty crazy (in a good way). All my favorite sci-fi, comedies and thrillers in one list. Impressed. Going to check all the ones I haven't seen
They all look interesting. Many years ago, netflix did the same. It recommended me a bunch of movies that seemed really interesting and I liked a ton of them, but these days netflix is a low bar. I'd bet they could do a great job, but have a more limited movie selection. Either that or the algo has actually declined.
Are you just on streaming? I've noted that the recommendations for streaming are fairly restrictive since they only have around 6000 movies available at a time.
With DVDs, the greater selection means better recommendations.
> the recommendations were better than those I get from Netflix
I can tell you exactly why Netflix makes such poor recommendations, and why almost anyone can do better with modest effort:
Netflix has to give recommendations for you from the 6000 movies that it's currently showing[1]. They can't recommend movies that they don't have. Whereas Taste.io can choose from the entire universe of ~500,000 movies.
An example should make this clear: If you liked The Godfather, it's an easy prediction that you'll like The Godfather: Part II and Part III. Suppose Netflix is currently showing The Godfather, but not the sequels. They cannot recommend the sequels to you. But Taste.io is not bound by that restriction; they can in theory recommend any movie that exists. It's much easier to find matches among 500,000 movies than among 6000.
[1] Netflix has just 6332 movies in the USA as of this date and even less in other countries (eg., 4365 in Canada). Most people are surprised by how few movies Netflix actually has. The Netflix user interface makes it very difficult to get a good impression of the number of movies; you can't just scroll alphabetically through the entire list for example.
Source: http://netflixcanadavsusa.blogspot.ca/
Presumably Netflix are using a wider system to choose which movies to licence? I wonder what their process for adding movies is - do they have a list from each studio they work with and select a movie to add, out do the negotiated each one separately.
Seems they could have a not yet available category that would let people pre-order; they could recommend a far wider swathe of content then.
I get what you're saying, but Netflix seems even worse than that. To wit: taste.io recommended movies for me - which I enjoy and that are in Netflix's current catalog - that Netflix hasn't recommended for me.
Cool user flow. I bet you could hit me with another facebook login request with the "see your results" popup, and I might not even mind it. That said, I won't click it.
We've tested other models but collaborative filtering gave us the most "human"/natural results. Also, didn't Netflix toss the matrix factorization after the contest? IIRC they decided to keep their current algorithm.
Interestingly, my sense has been that Netflix's recommendation engine does a poorer job now than it did 10 years ago. I always assumed that it was because they used to use fairly straightforward collaborative filtering, and now they seem to be heavily focused on looking for stuff that's somehow cosmetically similar to other stuff I've watched.
So, like, instead of saying, "You liked Nosferatu? Well, other people who liked Nosferatu also liked Ran, so let's suggest that," it now goes, "Hey, that's a vampire movie! How about Blade?"
I love the fact that the ratings are semantic, and limited to four easy to understand values rather than 5 stars:
Awful (Can I have those two hours back?)
Meh (Not great, but better than nothing
to kill time, escape or veg out)
Good (I enjoyed watching it)
Amazing (I'd watch it again and recommend
it to friends without hesitation)
With 5 stars, everyone interprets 2, 3 and 4 stars differently, e.g.:
Horrible Bad Meh Good Best
Bad Meh Good Very-Good Faves
Even the same person over time will not use a 5-star scale consistently. Even when I try to be consistent (I use the latter values for Netflix), if I like a movie but don't love it I don't know whether to give it 3 or 4 stars. On different days in different moods I'll make different choices.
I've no doubt that unreliable ranking data made Netflix recommendations harder, and impacted their mix of recommendation algorithms -- i.e. leaning more heavily on those that work despite rating scale inconsistencies. I'd expect the mix that works best for Taste.io will be different.
I have to agree that the rating options are very refreshing and easier to keep consistency over time. It also forces a choice between positive and negative which I'd imagine helps the algorithm learn things faster. Hmm...
I already maintain a list of movies to watch based on whatever interests me on netflix + random lists on internet. I took their quiz and their recommendations had good overlap with my existing list. Impressive!
1. Correctly identified a bunch of movies I had seen and really liked + some promising ones I hadn't seen, and
2. Showed me that I don't like any new movies
None of the 2016 movies were over 70% for me, whereas it identified some movies I had seen and loved as 97+%.
I had a similar experience. Every highly rated recommendation was either one of my favorite movies or on my list of movies I need to see very soon but haven't made the time for yet.
It knew to put The Holy Mountain at 100% based off me loving the new Mad Max, feeling ambivalent about the Star Wars prequels, hating the 2007 Tranformers movie, and thinking Anchor Man was good but not great. Like, how the hell? It's spot on, but how did it get that from my input? Is there more info on how this thing is getting its results? I would love to see even a sketchy outline of the algorithm.
Suggestion of 'Spirited Away' based purely on my ratings of X-Men and Saw? Spot on! I would love to read about the algorithm you guys are using (in an upcoming paper perhaps? :))
Nice! I'd love to be able to point it to my IMDB data. Both because it's got a comprehensive list of my ratings, but also so that it knows which movies I've seen to avoid recommending them!
I've rated many films on Netflix. It would be cool to be able to import my ratings from Netflix (or similar services like Amazon Video or IMDb) into Taste.io. Your service would get a lot more data to work with. :)
So far the recommendations have been very good and I've bookmarked a couple films to watch later.
Nice, the rating consensus system makes me curious about some stats, like for all users, the best movies with high consensus, and a list of good movies with least consensus.
It's an emotion vs intellect thing. Birdman is like cocaine to people who like the emotional side, and like hydrochloric acid for people who want a movie to be rational.
I'm just surprise the numbers even bear that out like that.
101 comments
[ 2.1 ms ] story [ 162 ms ] threadWhere does it get your move list from? I know I rated a lot of movies on my rotten-tomatoes profile, can this be used?
EDIT: Also, it's not clear that you can start using the product without Facebook, I like the fact that it lets you rate a couple movies before asking you to sign-up (with Facebook or with a regular email/password)
Am I blind or did I miss the button for 'I did not see this movie'? Because I didn't see quite a lot of the ones that I was asked my opinion on.
All in all, I always like these kind of things, but asking me if I like that Star Wars drivel 3 times in a row and then asking me if I liked 4 movies I never saw skewed my results a bit I think.
Keep improving though! If I can get only one 'wow' movie I never saw recommended, I would be really happy.
And came up with amazing recommendations of really cool movies I've either watched and loved, or haven't seen but always wanted to. Even the top pick for "movies from this year" was the one movie where I saw a trailer and said WANT.
That is, I'm curious how so many folks are claiming it is doing a great job.
With DVDs, the greater selection means better recommendations.
I can tell you exactly why Netflix makes such poor recommendations, and why almost anyone can do better with modest effort:
Netflix has to give recommendations for you from the 6000 movies that it's currently showing[1]. They can't recommend movies that they don't have. Whereas Taste.io can choose from the entire universe of ~500,000 movies.
An example should make this clear: If you liked The Godfather, it's an easy prediction that you'll like The Godfather: Part II and Part III. Suppose Netflix is currently showing The Godfather, but not the sequels. They cannot recommend the sequels to you. But Taste.io is not bound by that restriction; they can in theory recommend any movie that exists. It's much easier to find matches among 500,000 movies than among 6000.
[1] Netflix has just 6332 movies in the USA as of this date and even less in other countries (eg., 4365 in Canada). Most people are surprised by how few movies Netflix actually has. The Netflix user interface makes it very difficult to get a good impression of the number of movies; you can't just scroll alphabetically through the entire list for example. Source: http://netflixcanadavsusa.blogspot.ca/
Seems they could have a not yet available category that would let people pre-order; they could recommend a far wider swathe of content then.
https://torrentfreak.com/netflix-uses-pirate-sites-to-determ...
Really? I've always heard such negative things about Part III that I never bothered to watch it.
Matrix factorisation won the Netflix prize: http://dl.acm.org/citation.cfm?id=1608614 . What made you go for user closeness?
So, like, instead of saying, "You liked Nosferatu? Well, other people who liked Nosferatu also liked Ran, so let's suggest that," it now goes, "Hey, that's a vampire movie! How about Blade?"
I've no doubt that unreliable ranking data made Netflix recommendations harder, and impacted their mix of recommendation algorithms -- i.e. leaning more heavily on those that work despite rating scale inconsistencies. I'd expect the mix that works best for Taste.io will be different.
1. Correctly identified a bunch of movies I had seen and really liked + some promising ones I hadn't seen, and 2. Showed me that I don't like any new movies
None of the 2016 movies were over 70% for me, whereas it identified some movies I had seen and loved as 97+%.
How does this work?
It knew to put The Holy Mountain at 100% based off me loving the new Mad Max, feeling ambivalent about the Star Wars prequels, hating the 2007 Tranformers movie, and thinking Anchor Man was good but not great. Like, how the hell? It's spot on, but how did it get that from my input? Is there more info on how this thing is getting its results? I would love to see even a sketchy outline of the algorithm.
Recommendation are excellent - I noticed that recommendations are NOT about movie genre but about how the movies are made, their point, story, etc.
I.e., I hate when Netflix thinks that I like all stupid vampire movies because I liked Thirst [1].
[1] http://www.imdb.com/title/tt0762073/
E.g. 'Available streaming on Netflix'
So far the recommendations have been very good and I've bookmarked a couple films to watch later.
EDIT: The release date is included in the URL for the movie.
Highest Consensus:
1. Whiplash
2. 12 Angry Men
3. Se7en
Most Controversial:
1. Birdman
2. Citizen Kane
3. 2001: A Space Odyssey
I knew that abomination was polarizing, but i did not quite expect that.
It's an emotion vs intellect thing. Birdman is like cocaine to people who like the emotional side, and like hydrochloric acid for people who want a movie to be rational.
I'm just surprise the numbers even bear that out like that.