Recent work in Ontology learning and Text mining has mainly focused on engineering methods to solve practical problem. In this thesis, we investigate methods that can substantially...
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Ontology matching plays a key role for semantic interoperability. Many methods have been proposed for automatically finding the alignment between heterogeneous ontologies. However...
Feng Shi, Juanzi Li, Jie Tang, Guo Tong Xie, Hanyu...
We present a corpus-based approach to the class expansion task. For a given set of seed entities we use co-occurrence statistics taken from a text collection to define a membersh...
We present an approach for online learning of discriminative appearance models for robust multi-target tracking in a crowded scene from a single camera. Although much progress has...