Knowledge Sifter is a scaleable agent-based system that supports access to heterogeneous information sources such as the Web, open-source repositories, XML-databases and the emergi...
Larry Kerschberg, Mizan Chowdhury, Alberto Damiano...
We propose a model that leverages the millions of clicks received by web search engines to predict document relevance. This allows the comparison of ranking functions when clicks ...
The currently booming search engine industry has determined many online organizations to attempt to artificially increase their ranking in order to attract more visitors to their ...
The proliferation of knowledge-sharing communities like Wikipedia and the advances in automated information extraction from Web pages enable the construction of large knowledge ba...
We propose a framework for searching the Wikipedia with contextual information. Our framework extends the typical keyword search, by considering queries of the type q, p , where q...
Antti Ukkonen, Carlos Castillo, Debora Donato, Ari...