This screencast from Particls shows us new functionalities like attention driven RSS feeds presented in different ways based on relevancy. It is similar to NetVibes, yet more advanced due to prioritization of feeds. It is about attention instead of just plain information. Clearly, in line with the current work and thinking on Intention Economy, Social Networking, Personalization and Attention.xml. And it can be integrated with the service of Jaiku which is similar to a lifestream - centered around users - with photos, twitter streams, locations, blog posts etc. In my view you can segment websites in different ways: themes/categories/verticals, user/people, time/historic/futuristic, location/places and data. Clearly, Particls is built up from the user inside out. What I like personally is the option to integrate granular LinkedIn search categories. Thanks to Jeremy Wagstaff from Wall Street Journal. The whole post is here. Recommended !
"Particls (www.particls.com) looks simple enough: a downloadable ticker that runs across the top of your screen, pumping you information. Nothing new about this; the difference lies in what information it presents, and how it appears. Instead of shoveling data at you, Particls tries to figure out what you're paying attention to. Enter a few keywords of things you're interested in and Particls scours millions of blogs and news sources to find stuff that matches them. You can then tweak this flow by raising or lowering the relevance of any particular feed or keyword (from strongly like to strongly dislike).
What I like about Particls is that it starts not from an "information" point of view but an "attention" one: matching and presenting the information according to the time you can give it, so the amount of information you receive varies, as well as the type of information. Particls doesn't so much grab armfuls of stuff for you as cherry pick it."