• norsk
    • English
  • English 
    • norsk
    • English
  • Login
View Item 
  •   Home
  • Fakultet for informasjonsteknologi og elektroteknikk (IE)
  • Institutt for informasjonssikkerhet og kommunikasjonsteknologi
  • View Item
  •   Home
  • Fakultet for informasjonsteknologi og elektroteknikk (IE)
  • Institutt for informasjonssikkerhet og kommunikasjonsteknologi
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Ontology-based Data Extraction in the Scholarship-Related Content

Yushtina, Anna
Master thesis
Thumbnail
View/Open
AYushtina2013.pdf (6.974Mb)
URI
http://hdl.handle.net/11250/144038
Date
2013
Metadata
Show full item record
Collections
  • Institutt for informasjonssikkerhet og kommunikasjonsteknologi [1600]
Abstract
Master Thesis on the topic "Ontology-based Data Extraction in the Scholarship-Related Content"

is concentrated on the area of ontologies and on the research of the methods by which ontological

concepts can be recognized in the text, enhancing its semantic meaning.

The use of ontologies can significantly improve semantic richness of the texts presented on

the Web, but to be able to exploit all their capabilities, specific XML-based notations must be

written to describe each and every resource. This is usually quite a big amount of human work,

and the Thesis is seeking for the ways to decrease the amount of human resources, either by

suggesting automatic or semi-automatic approaches for ontology-based information retrieval.

In the experiments conducted in the domain of scholarships, ontology for scholarships has

been thoroughly evaluated, and the names of the disciplines were chosen as a target area for the

further information retrieval research.

Discovery of the ontological concepts in the text was performed by, first, scraping the webpage

for the target section, and then by implementing Boolean search method with and without prior

preprocessing. Such approach demonstrated very good results, and with preprocessing roughly

70% of the disciplines were retrieved. Furthermore, extension of the ontology has been proposed

as the way to increase extraction rate by 10%. Overall, 80% of the disciplines can be retrieved

by our method.

Contact Us | Send Feedback

Privacy policy
DSpace software copyright © 2002-2019  DuraSpace

Service from  Unit
 

 

Browse

ArchiveCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsDocument TypesJournalsThis CollectionBy Issue DateAuthorsTitlesSubjectsDocument TypesJournals

My Account

Login

Statistics

View Usage Statistics

Contact Us | Send Feedback

Privacy policy
DSpace software copyright © 2002-2019  DuraSpace

Service from  Unit