We present a semi-supervised machine-learning approach for the classification of adjectives into property- vs. relationdenoting adjectives, a distinction that is highly relevant f...
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
— We propose a new approach to the problem of schema matching in relational databases that merges the hybrid and composite approach of combining multiple individual matching tech...
We build the generic methodology based on machine learning and reasoning to detect the patterns of interaction between conflicting agents, including humans and their assistants. L...
The Web is now a huge information repository with a rich semantic structure that, however, is primarily addressed to human understanding rather than automated processing by a compu...