Alani, Harith; Noy, Natasha; Shah, Nigam; Shadbolt, Nigel and Musen, Mark
(2007).
![[img]](http://oro.open.ac.uk/style/images/fileicons/application_pdf.png)
|
PDF (Accepted Manuscript)
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (86kB) |
| URL: | http://protege.stanford.edu/conference/2007/ |
|---|---|
| Google Scholar: | Look up in Google Scholar |
Abstract
As more ontologies become publicly available, finding the 'right' ontologies becomes much harder. In this paper, we introduce a new ontology search technique which is based on corpus analysis. In particular, we look at the case when users search for ontologies relevant to a particular topic (e.g., an ontology about anatomy). Our experiments demonstrate that using our method for query expansion improves retrieval results by a 113%, compared to the tools that search only for the user query terms and consider only class and property names.
| Item Type: | Conference or Workshop Item |
|---|---|
| Copyright Holders: | 2007 The Authors |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi) Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Interdisciplinary Research Centre: | Centre for Research in Computing (CRC) Centre for Policing Research and Learning (CPRL) |
| Item ID: | 21190 |
| Depositing User: | Harith Alani |
| Date Deposited: | 19 Apr 2010 14:33 |
| Last Modified: | 23 Jun 2017 05:33 |
| URI: | http://oro.open.ac.uk/id/eprint/21190 |
| Share this page: |     |
Download history for this item
These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.