Improving web data annotations with spreading activation

The Web has established itself as the largest public data repository ever available. Even though the vast majority of information on the Web is formatted to be easily readable by the human eye, "meaningful information" is still largely inaccessible for the computer applications. In this paper, we present automated algorithms to gather meta-data and instance information by utilizing global regularities on the Web and incorporating the contextual information. Our system is distinguished since it does not require domain specific engineering. Experimental evaluations were successfully performed on the TAP knowledge base and the faculty-course home pages of computer science departments containing 16,861 Web pages.