Information extraction and text summarization using linguistic knowledge acquisition
Information Processing and Management: an International Journal
Topic parsing: accounting for text macro structures in full-text analysis
Information Processing and Management: an International Journal - Special issue on natural language processing and information retrieval
The identification of important concepts in highly structured technical papers
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Evaluating Natural Language Processing Systems: An Analysis and Review
Evaluating Natural Language Processing Systems: An Analysis and Review
Mixed-initiative development of language processing systems
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Independence and commitment: assumptions for rapid training and execution of rule-based POS taggers
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Concept identification and presentation in the context of technical text summarization
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLPWorkshop on Automatic summarization - Volume 4
Adapting a Robust Multi-genre NE System for Automatic Content Extraction
AIMSA '02 Proceedings of the 10th International Conference on Artificial Intelligence: Methodology, Systems, and Applications
Automatic summarising: The state of the art
Information Processing and Management: an International Journal
dg.o '08 Proceedings of the 2008 international conference on Digital government research
An instance learning approach for automatic semantic annotation
CIS'04 Proceedings of the First international conference on Computational and Information Science
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In this paper we describe how information extraction technology has been used to build a summarisation system in the domain of occupational health and safety. The core of the application is based on named entity recognition using pattern-action semantic grammar rules. Co-occurrence of the named entities is used as a criteria to identify the sentences to be included in the summary. The system is developed and automatically evaluated within the GATE framework, and can easily be extended or ported to new domains.