We describe a new family of topic-ranking algorithms for multi-labeled documents. The motivation for the algorithms stems from recent advances in online learning algorithms. The a...
Eye tracking experiments have shown that titles of Web search results play a crucial role in guiding a user’s search process. We present a machine-learned algorithm that trains ...
Tapas Kanungo, Nadia Ghamrawi, Ki Yuen Kim, Lawren...
In order to deal with the diversified nature of XML documents as well as individual user preferences, we propose a novel Multiodel (MRM), which is able to abstract a spectrum of i...
Traditional web link-based ranking schemes use a single score to measure a page’s authority without concern of the community from which that authority is derived. As a result, a...
The practical implementation and use of a mediator for fixed income securities analysis demonstrated the potential for extending the application of conceptual modeling from the sys...