Unsupervised event extraction from biomedical text based on event and pattern information

Hong Woo Chun, Young Sook Hwang, Hae Chang Rim

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this paper, we proposed a new event extraction method from biomedical texts. It can extend patterns by unsupervised way based on event and pattern information. Evaluation of our system on GENIA corpus achieves 90.1% precision and 70.0% recall.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsAlexander Gelbukh
PublisherSpringer Verlag
Pages533-536
Number of pages4
ISBN (Print)3540210067, 9783540210061
DOIs
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2945
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Unsupervised event extraction from biomedical text based on event and pattern information'. Together they form a unique fingerprint.

  • Cite this

    Chun, H. W., Hwang, Y. S., & Rim, H. C. (2004). Unsupervised event extraction from biomedical text based on event and pattern information. In A. Gelbukh (Ed.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 533-536). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2945). Springer Verlag. https://doi.org/10.1007/978-3-540-24630-5_66