Conference Paper

A Framework for Integrating Deep and Shallow Semantic Structures in Text Mining.

DOI: 10.1007/978-3-540-45224-9_110 Conference: Knowledge-Based Intelligent Information and Engineering Systems, 7th International Conference, KES 2003, Oxford, UK, September 3-5, 2003, Proceedings, Part I
Source: DBLP

ABSTRACT Recent work in knowledge representation undertaken as part of the Semantic Web initiative has enabled a common infrastructure (Resource De- scription Framework (RDF) and RDF Schema) for sharing knowledge of on- tologies and instances. In this paper we present a framework for combining the shallow levels of semantic description commonly used in MUC-style informa- tion extraction with the deeper semantic structures available in such ontologies. The framework is implemented within the PIA project software called Ontol- ogy Forge. Ontology Forge offers a server-based hosting environmentfor ontolo- gies, a server-side information extraction system for reducing the effort of writ- ing annotations and a many-featured ontology/annotation editor. We discuss the knowledge framework, some features of the system and summarize results from extended named entity experiments designed to capture instances in texts using support vector machine software.