We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
We discuss the problem of Web data extraction and describe an XML-based methodology whose goal extends far beyond simple "screen scraping." An ideal data extraction proc...
Unprecedented amounts of media data are publicly accessible. However, it is increasingly difficult to integrate relevant media from multiple and diverse sources for effective appli...
Background: Information obtained from diverse data sources can be combined in a principled manner using various machine learning methods to increase the reliability and range of k...
Bolan Linghu, Evan S. Snitkin, Dustin T. Holloway,...
We address the problem of large-scale data integration, where the data sources are unknown at design time, are from autonomous organisations, and may evolve. Experiments are descr...
Fujun Zhu, Mark Turner, Ioannis A. Kotsiopoulos, K...