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BMC Bioinformatics. 2006 Nov 24;7 Suppl 3:S3.

An environment for relation mining over richly annotated corpora: the case of GENIA.

Author information

  • 1Institute of Computational Linguistics, IFI, University of Zurich, Switzerland. rinaldi@ifi.unizh.ch

Abstract

BACKGROUND:

The biomedical domain is witnessing a rapid growth of the amount of published scientific results, which makes it increasingly difficult to filter the core information. There is a real need for support tools that 'digest' the published results and extract the most important information.

RESULTS:

We describe and evaluate an environment supporting the extraction of domain-specific relations, such as protein-protein interactions, from a richly-annotated corpus. We use full, deep-linguistic parsing and manually created, versatile patterns, expressing a large set of syntactic alternations, plus semantic ontology information.

CONCLUSION:

The experiments show that our approach described is capable of delivering high-precision results, while maintaining sufficient levels of recall. The high level of abstraction of the rules used by the system, which are considerably more powerful and versatile than finite-state approaches, allows speedy interactive development and validation.

PMID:
17134476
[PubMed - indexed for MEDLINE]
PMCID:
PMC1764447
Free PMC Article

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