A framework for integrating deep and shallow semantic structures in text mining

Nigel Collier, Koichi Takeuchi, Ai Kawazoe, Tony Mullen, Tuangthong Wattarujeekrit

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)

Abstract

Recent work in knowledge representation undertaken as part of the Semantic Web initiative has enabled a common infrastructure (Resource Description Framework (RDF) and RDF Schema) for sharing knowledge of ontologies and instances. In this paper we present a framework for combining the shallow levels of semantic description commonly used in MUC-style information extraction with the deeper semantic structures available in such ontologies. The framework is implemented within the PIA project software called Ontology Forge. Ontology Forge offers a server-based hosting environment for ontologies, a server-side information extraction system for reducing the effort of writing 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.

Original languageEnglish
Pages (from-to)824-834
Number of pages11
JournalLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume2773 PART 1
Publication statusPublished - Dec 1 2003
Externally publishedYes
Event7th International Conference, KES 2003 - Oxford, United Kingdom
Duration: Sep 3 2003Sep 5 2003

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'A framework for integrating deep and shallow semantic structures in text mining'. Together they form a unique fingerprint.

Cite this