FeedHub is aimed at this crowd. After controlled alpha testing, it's now generally available in a beta version. To use it, go to the FeedHub site, and follow a two-step process: Upload your OPLM file, then subscribe with your preferred feed reader. FeedHub becomes the filter through which your RSS sources pass.
FeedHub applies machine learning to your RSS habits, applying greater weight to most-read topics and less to those you tend to ignore. As such, it's an automated tool. "We make your feed reader smarter," says Sean Ammirati, VP of business development and product management for Pittsburgh-based mSpoke. The technology behind it is mSpoke's mPower Adaptive Personalization Engine.
mSpoke has put control knobs on FeedHub so users can assign different levels of value to different topics. Key here are "memes," predefined topics and categories, such as the most popular Digg entries. So you've got machine learning (the mPower engine), human clustering (Digg, Del.icio.us), and user preferences all combined into one RSS filtering system.
One application that sounds promising to me: Accessing news and blogs through a FeedHub-enabled smartphone, a potentially fast and easy way to get your most significant news feeds while on the road.
mSpoke hopes to make money through advertising, but that requires volume, so first things first. "No. 1 now is to create a compelling experience for users," says Ammirati.
