In this paper, we present an extension of PHIL, a declarative language for filtering information from XML data. The proposed approach allows us to extract relevant data as well a...
Recent progress in information extraction technology has enabled a vast array of applications that rely on structured data that is embedded in natural-language text. In particular...
Automatic metadata generation provides scalability and usability for digital libraries and their collections. Machine learning methods offer robust and adaptable automatic metadat...
Hui Han, C. Lee Giles, Eren Manavoglu, Hongyuan Zh...
The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...
This paper presents an approach which supports verification and model-based adaptation of software compod services implemented using Windows Workflow Foundation (WF). First, we pr...