Personalized Recommendations Are Still Hit Or (Mostly) Miss
from the thumbs-up,-thumbs-down dept
Just as Google is throwing its hat into the personalized news recommendation ring, the NY Times has an article looking at a variety of recommendation systems and basically concludes that it's tough to have recommendations that actually are all that useful. Some systems, such as those used by Amazon, Netflix and iTunes (all using some form of collaborative filtering) have pretty strong reputations -- but even then, it's amazing just how many of the recommendations people see that simply don't match them at all. The real issue is that automated personalization is an extremely hard problem to solve algorithmically, and it still seems like the "best" ones are only picking out relevant info only a small fraction of the time.
Thank you for reading this Techdirt post. With so many things competing for everyone’s attention these days, we really appreciate you giving us your time. We work hard every day to put quality content out there for our community.
Techdirt is one of the few remaining truly independent media outlets. We do not have a giant corporation behind us, and we rely heavily on our community to support us, in an age when advertisers are increasingly uninterested in sponsoring small, independent sites — especially a site like ours that is unwilling to pull punches in its reporting and analysis.
While other websites have resorted to paywalls, registration requirements, and increasingly annoying/intrusive advertising, we have always kept Techdirt open and available to anyone. But in order to continue doing so, we need your support. We offer a variety of ways for our readers to support us, from direct donations to special subscriptions and cool merchandise — and every little bit helps. Thank you.
–The Techdirt Team
Reader Comments
Subscribe: RSS
View by: Time | Thread
My TiVo thinks I�m gay
In all honesty though, pushing people to a narrow field of information often makes those people bored... and they will often go elsewhere for "variety".
Just because I enjoy watching movies about gladiators, prison fights and gangs, doesn't mean that I like movies about men - it means that I like action movies and could care less about plot and story line. I prefer a good James Bond, Stallone and Arnold movie when they are on - but give me an entire channel of women, and im hooked! (i don't mean Home & Garden network or TLC)
I think the same could be said about all these other "we recommend" systems - they really don't know what individuals want. Only the individual knows this.
[ link to this | view in thread ]
Not all that useful?
How did you get that from the article? From my read, the article says exactly the opposite.
At the beginning, she says, "Companies are finding that getting those personalized recommendations right - or even close - can mean significantly higher sales."
On Netflix, she says, "roughly two-thirds of the films rented were recommended to subscribers by the site" and that Netflix "credits the system's ability to make automated yet accurate recommendations as a major factor in its growth from 600,000 subscribers in 2002 to nearly 4 million today."
[ link to this | view in thread ]
Re: Not all that useful?
[ link to this | view in thread ]
Re: Not all that useful?
My roommate last night was looking for Freshmen, the comic by Seth Green. Well there's a magazine, Fresh Men, that came up in his search so now amazon thinks he likes young men freshly 18,
If they let you click a box that says I'm not really interested in other things like this they might end up with better recommendations.
[ link to this | view in thread ]
Pandora
[ link to this | view in thread ]
More targeted recommendations
But I love their "Friends" feature! I have pretty eclectic tastes, and several friends also into weird and obscure things, and seeing what they watch and rate is far more useful. If I know what somebody likes and dislikes, their ratings mean far much more to me. I've discovered some neat films that way, and also turned several people onto hidden gems and classics that way. The only downside is my queue keeps ballooning out of control as a result.
I'd like to see more of that. Amazon could say something like "Brian loved this book", and since I know his tastes it's a far more useful recommendation to me than "People that bought this also bought that."
[ link to this | view in thread ]
Netflix recommendations are a mess
[ link to this | view in thread ]