Tools for semantic annotation of taxonomic descriptions

Hong Cui, Partha Pratim Sanyal, Chunshui Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A software application for automated semantic annotation of taxonomic, especially morphological, descriptions is reported in this paper. The tool is based on unsupervised machine learning methods. It is designed to annotate descriptions in a deviated syntax that is not normal English but often used in morphological descriptions. The unsupervised annotation system does not need any training examples to annotate text descriptions. It uses a relevant glossary available to it but aims to learn as much information as possible from the text itself. Tools such as this are needed to reformat free-text or OCRed taxonomic documents to a semantic-explicit format for easy and intelligent access, providing character data for phylogenetic research, climate impact on biodiversity, and traditional biosystematics research.

Original languageEnglish (US)
Title of host publicationKnowledge-Based and Intelligent Information and Engineering Systems - 14th International Conference, KES 2010, Proceedings
Pages506-516
Number of pages11
EditionPART 4
DOIs
StatePublished - 2010
Event14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2010 - Cardiff, United Kingdom
Duration: Sep 8 2010Sep 10 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 4
Volume6279 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2010
Country/TerritoryUnited Kingdom
CityCardiff
Period9/8/109/10/10

Keywords

  • Morphological descriptions
  • Semantic annotation
  • Software applications
  • Supervised machine learning
  • Unsupervised machine learning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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