Visual encyclopedia builds itself by scouring the internet
Crowdsourced knowledge bases like Wikipedia encompass a lot
of knowledge, but humans can only add to them so quickly. Wouldn't it be
better if computers did all the hard work? The University of Washington
certainly believes so. Its LEVAN (Learn EVerything about ANything) program is building a visual encyclopedia by automatically searching the Google Books
library for descriptive language, and using that to find pictures
illustrating the associated concepts. Once LEVAN has seen enough, it can
associate images with ideas simply by looking at pixel arrangements.
Unlike earlier learning systems, such as Carnegie Mellon's NEIL,
it's smart enough to tell the difference between two similar objects
(such as a Trojan horse and a racing horse) while lumping them under one
broader category.
Read the Full Story
We are Creative Blogger Theme Wavers which provides user friendly, effective and easy to use themes.
Each support has free and providing HD support screen casting.
