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Frequently Asked Questions

What is Feeds 2.0?

Feeds 2.0 is a Web 2.0 personalized RSS aggregator. It incorporates a learning engine so that it does much more than show posts as they come in. Instead, it prioritizes incoming information according to the user's interests!

How does it differ from other RSS Aggregators?

Traditional RSS readers just don't work efficiently since in a flood of information it can be hard to find important and interesting news. For example, feeds that post frequently, tend to dominate posts. Sources that post less frequently might be buried much deeper. Feeds 2.0 ranks the feeds according to the user's preferences and brings interesting articles in the first couple of pages.

How does it work?

Feeds 2.0 utilizes an advanced computational intelligence personalization learning engine. With personalization the system ranks the feeds according to sources a particular user likes, authors and topics he's interested in, and brings interesting articles first. These are ranked by a score the system has assigned based on what has learned about the user's preferences. The system creates a dynamic profile of the topics the user likes and the sources he reads most. It actually begins to learn immediately from the first couple of clicks in order to figure out the user's preferences but obviously the more he uses it the better it gets.

How do I use it?

It's really very simple. As soon as a user starts reading, the system will learn what he likes to read and what he doesn't care much about. Actually, there are two ways with which the system learns your preferences: You can either click on the title of each post to read or just click on the heart icon of each post if you are in hurry or if you don't care to read the entire article but you still like it. By clicking on the down arrow icon of each post you inform the system that you are not particularly interested in the subject of the post.

Can I import my favourite feeds?

Of course. Users can import an OPML file with their existing feeds or add feeds individually.

What's the "automatic clustering feature"?

Feeds 2.0 does real time automated clustering of similar items aggregated from different sources. This automatically solves the problem that many users are facing when subscribing to feeds with similar subjects, like for example News Feeds. Items covering the same story originating from, say, sources like Google News or BBC News Top Stories will appear all on the same cluster and therefore the effect of having practically the same item appearing again and again is eliminated. Needless to say how much time this saves when one is subscribed to many many feeds with similar subjects.

What's the recommendation feature? How do recommendations work?

The recommendation feature takes into account what the entire community of Feeds 2.0 readers are finding interesting and recommends related posts and feeds that a user might want to read. It uses a technology called collaborative filtering to generate recommendations. It works by matching together users with similar reading tastes. Each member of the system has a 'neighbourhood' of other like-minded users. Ratings from these neighbours are used to create personalized recommendations for the target user.

What about social bookmarking, tagging and sharing?

An important feature of Feeds 2.0 is a natural language recognition mechanism we have implemented. This allows us to identify the language in which any feed item is written in, despite the fact that all items share the same universal UTF character encoding. The natural language detection allows us to automatically extract the most important keywords as tags for each item. Obviously this leads to an automatic creation of a sort of Tag Cloud which users can use in order to find feeds and items related to a particular subject. Of course users are also able to do their own tagging in order to build a kind of social bookmarking and sharing network within the Feeds 2.0 community of users.

Does it really work?

You bet! However, don't take our word for it. The only way to really find out is to try it for yourself!

Can I turn personalization off and use it as a standard RSS aggregator?

Users can always turn the personalization feature off at any time in order to read the more recent posts in a kind of river style of news browsing (sorted by publication date).

Which keyboard shortcuts are supported?

Keyboard shortcuts can save you a lot of time by navigating you quickly through your posts / feeds. The supported keyboard shortcuts are:

j / kRead the next/previous displayed post
space / shift-spaceMove the page down/up
n / pSelect the next/previous post without marking it as read or expanding it
o, enterExpand or collapse the selected post
i or sMark selected post as interesting (love)
uMark selected post as uninteresting (hate)
mSwitches the read state of the selected post (read / unread)
vRead original source of the selected post in a new window (visit link)
shift-aMark all displayed posts as read
1Expand all displayed posts
2Collapse all displayed posts
rRefresh the unread counts in the folder tree
g then aGo to "All posts"
g then s or iGo to "Loved posts"
g then uGo to "Ignored posts"
g then nGo to "Unread posts"
g then rGo to "Read posts"

Who are you and why did you create Feeds 2.0?

Feeds 2.0 has been established by three scientists and professionals with significant experience in Information Technology. Its main area of expertise is the utilization of advanced computational intelligence techniques in information retrieval.

We created Feeds 2.0 simply because at some point we found it impossible to cope with information overload. Considering also the fact that RSS is still in its early stage of adoption, we believe that it is of extreme important to timely create tools that will help users to utilize RSS effectively.

Does Feeds 2.0 has a Privacy Policy?

Yes, it does. Please read it and let us know if you have any problems or concerns.

Who do I contact if I have problems?

You can contact us here.

How do I start?

Sign up for a beta account.

Feeds 2.0 is


. We're currently in private beta with plans for a public beta soon.

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