Open Intelligence | My Amplog

When we first looked at Faviki, a social bookmarking application which made its debut last year, we were intrigued by their idea of “semantic tagging.” What makes Faviki different from its competitors, services like del.icio.us, Diigo, and the now-defunct Ma.gnolia, is the way the service suggests tags to its users. The suggestions don’t come from the community of Faviki users and their tagging history - they come from structured info extracted from the Wikipedia database.

This is an important change for the service because it means users can tag web pages any which way they want, but they’re still linked to the structured data on the back-end. That way, when someone searches through Faviki’s community tags, all the web pages for that particular item or concept will appear, even if people tagged them using their own personal keywords.

Another change in Faviki’s service is the ability to define new tags. Prior to today, the service was limited to searching Wikipedia for tag suggestions, but now it has the whole web at its fingertips. If a tag is entered which doesn’t match anything from Wikipedia, Faviki will search Google for relevant URLs and then ask if the links presented represent the same tag. As multiple users go through this process, Faviki learns what URLs best represent that concept and adds the new tags created by the users to its database. Read more at www.readwriteweb.com