Persai, a new filtering program that aims to cure the Web's information overload.

Persai, a new filtering program that aims to cure the Web's information overload.

Persai, a new filtering program that aims to cure the Web's information overload.

Innovation, the Internet, gadgets, and more.
Feb. 20 2008 3:48 PM

How To Be a Better Browser

Can a new filtering program cure the Web's information overload?

Persai. Click image to expand.

In a scant four years, the Internet, my beloved wellspring of information, has blown its top and become a geyser. Back in 2004, I heaped praise on an exciting new system called RSS. The "Really Simple Syndication" format promised to be TiVo for Web surfers—by automatically pulling content from all your favorite blogs and news sites, an RSS reader would make your Web surfing more fruitful and more efficient. While that prospect sounded enticing at the time, RSS has turned out to be more of a problem than a solution. As of this moment, I have 897 unread RSS items. I don't need a way to read more of the Net. I need a way to see less of it.

I've got two main beefs with RSS. The first is information overload. If I don't check in every few hours, my RSS reader fills with unread blog posts. Rather than feel relieved that I can catch up on my missed surfing, that long list of bold headlines gives me the sensation that I'm hopelessly behind and won't ever catch up. I've got enough to do at home and at work that I don't need Web surfing to seem like a chore.


The second issue is that my RSS reader is only as smart and attentive as I am. It hasn't figured out that I've stopped reading 14 of the 15 feeds I subscribed to when I worked there last year. It can't tell that I only care for about one in 20 of Dave Winer's nonstop posts, and it has no way of guessing which one that will be.

I'm down on RSS at the moment, but I'm not ready to abandon it just yet. That's why I'm excited about Persai, a new service that promises to solve my two big problems. The application, which is now in private beta test, bills itself as a smart filter, a way both to tame and to improve your RSS content.

Persai (pronounced per-SIGH) is a system for reading RSS-fed content, but it doesn't focus on individual feeds. Instead, it throws everything it can find into one big hopper, then asks about what you like so it can dole out suitable articles. You start by creating one or more "interests" based on keywords of your choice—say, "American Idol" or "astrophysics discovery." Once you've punched in your interests, Persai turns each one into a custom page. These pages look a lot like Google News search results—a collection of news articles and blog posts from the past day that match your interest. The matches aren't based on exact keywords, but rather on a more complex word-math algorithm that can figure out that a post about Carly Smithson matches my American Idol interest.

Persai won me over immediately because it's an anti-social network: It ignores everything and everyone on the Internet except for what I want to read. Rather than presume I'm like other people, Persai tracks my unique reading habits and, more importantly, remembers what I don't want. Telling the program I don't like something is as simple as clicking a red X labeled "reject." Persai notes which news articles and blog posts I despise, then filters out others like them by doing more math on what words show up in the articles and where they appear. It presumes that if I click an article to read it—and don't hit the reject button—I like it.

I tested Persai with several different interests. One topic stood out as the ultimate filtering challenge: Barack Obama. As the favorite candidate of college students and Democratic bloggers, the Illinois senator is the subject of a jillion posts a day. Some are fascinating. Most are stupid. I need an Obama Fever filter.