License
When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.08131.14
URN: urn:nbn:de:0030-drops-15150
URL: https://drops.dagstuhl.de/opus/volltexte/2008/1515/
Go to the corresponding Portal


Milward, David

Ontology-Based Interactive Information Extraction

pdf-format:
08131.MilwardDavid.ExtAbstract.1515.pdf (0.02 MB)


Abstract

Interactive Information Extraction brings together search and
information extraction to provide fast, interactive text mining over
large volumes of text such as Medline abstracts, full text scientific
articles, patents etc. As well as covering the two ends of the spectrum:
keyword search over documents, and detailed linguistic patterns within
sentences, the Interactive Information Extraction System, I2E, also
covers the points in between such as keywords within the same sentence,
or co-occurrence of biological entities within sentences or documents.
This talk briefly introduces the idea of Interactive Information
Extraction, and describes how terminologies/ontologies are incorporated.
We also show how I2E can be used to augment ontologies by finding
potential synonyms or members of classes from the literature using
linguistic patterns. Finally we discuss issues concerning how best to
use ontologies for text mining.



BibTeX - Entry

@InProceedings{milward:DagSemProc.08131.14,
  author =	{Milward, David},
  title =	{{Ontology-Based Interactive Information Extraction}},
  booktitle =	{Ontologies and Text Mining for Life Sciences : Current Status and Future Perspectives},
  pages =	{1--1},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8131},
  editor =	{Michael Ashburner and Ulf Leser and Dietrich Rebholz-Schuhmann},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2008/1515},
  URN =		{urn:nbn:de:0030-drops-15150},
  doi =		{10.4230/DagSemProc.08131.14},
  annote =	{Keywords: Information extraction, ontologies, text mining}
}

Keywords: Information extraction, ontologies, text mining
Collection: 08131 - Ontologies and Text Mining for Life Sciences : Current Status and Future Perspectives
Issue Date: 2008
Date of publication: 03.06.2008


DROPS-Home | Fulltext Search | Imprint | Privacy Published by LZI