Seed-based generation of personalized bio-ontologies for information extraction

Cui Tao, David W. Embley

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

9 Scopus citations

Abstract

Biologists usually focus on only a small, individualized, subdomain of the huge domain of biology. With respect to their sub-domain, they often need data collected from various different web resources. In this research, we provide a tool with which biologists can generate a sub-domain-size, user-specific ontology that can extract data from web resources. The central idea is to let a user provide a seed, which consists of a single data instance embedded within the concepts of interest, Given a seed, the system can generate an extraction ontology, match information with the user's view based on the seed, and collect information from online repositories. Our initial experimentations Indicate that our prototype system can successfully match source data with an ontology seed and gather information from different sources with respect to user-specific, personalized views.

Original languageEnglish (US)
Title of host publicationAdvances in Conceptual Modeling - Foundations and Applications - ER 2007 Workshops CMLSA, FP-UML, ONISW, QoIS, RIGiM, SeCoGIS, Proceedings
Pages74-84
Number of pages11
StatePublished - Dec 1 2007
Event26th International Conference on Conceptual Modeling, ER 2007 - Auckland, New Zealand
Duration: Nov 5 2007Nov 9 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4802 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other26th International Conference on Conceptual Modeling, ER 2007
CountryNew Zealand
CityAuckland
Period11/5/0711/9/07

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Tao, C., & Embley, D. W. (2007). Seed-based generation of personalized bio-ontologies for information extraction. In Advances in Conceptual Modeling - Foundations and Applications - ER 2007 Workshops CMLSA, FP-UML, ONISW, QoIS, RIGiM, SeCoGIS, Proceedings (pp. 74-84). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4802 LNCS).