Has anyone created an RSS-based recommendation engine yet?
Like reddit, but input/output of OPML/OPML instead of votes/links.
We're obviously all going to be using RSS some day so this is inevitable. I'm just wondering if someone's done it yet.
We're obviously all going to be using RSS some day so this is inevitable. I'm just wondering if someone's done it yet.
I hadn't thought about the possibility of producing OPML as the output, but it's certainly something I could add in a future version (it's still in a fairly early stage of development right now).
Most people who are fanatic about RSS aren't going to be able to manually input the URL to each of their feeds due to the sheer number of feeds they subscribe to.
There's a new design in the works for adding feeds, different from what's there now, but I hadn't thought of using OPML until you mentioned it.
I'll post it in the next few days, so check back later in the week if you get a chance.
Alternatively, if you have any other feedback, let me know here, or just email me (my address is in my profile).
Other changes are in the works, too; send me an email or reply to this thread if you'd like to be kept un-to-date on those as they happen.
EVEN better yet, your feed reader can assign weights to the feeds based on how often you actually read the content.
Building recommendation engines is really hard from an algorithmic perspective. How you format the inputs and outputs seems negligible in importance.
Google has a huge advantage in this area since they collect which items from an RSS feed people actually read on Google Reader. They know that even though I subscribe to the del.icio.us/popular and digg RSS feeds, I rarely read any of the items, whereas I read almost everything from dive into mark or Jeremy Zawodny's blog.
As far as the output is concerned, it doesn't have to be traditional "output" at all. It can be an increased PageRank for a site, or a Firefox extension that shows a reputation meter for every site you visit.
The format isn't important, but the things people subscribe to are very important.
The INPUT on the other hand is extremely important. Take a look at Reddit... you have to manually up/down vote articles to make the recommendation system go. Not only is that tedious, but I don't believe people actually have a good grasp of the content they are looking for.
RSS feeds, on the other hand, are much more relevant. And getting a list of someone's feeds requires no work on their part to describe to you their interests.
Even better, online readers/aggregators such as Google Reader have an even more extreme advantage in being able to tell what you read and how often you read it (as the other poster pointed out) more accurately than your OPML file. It's a gold mine for anyone trying to build content recommendation systems.
Take a look at Reddit... it's become a collective RSS feed aggregator plus stupid pictures of cats. If the recommendation engine worked, it would be a GOOD collective RSS feed aggregator. I believe you can get there by working with RSS feeds and actual reading statistics as inputs rather than manual link clicking.