Publication Type

Journal Article

Version

publishedVersion

Publication Date

1-2010

Abstract

Given its effectiveness to better understand data, ontology has been used in various domains including artificial intelligence, biomedical informatics and library science. What we have tried to promote is the use of ontology to better understand media (in particular, images) on the World Wide Web. This paper describes our preliminary attempt to construct a large-scale multi-modality ontology, called AutoMMOnto, for web image classification. Particularly, to enable the automation of text ontology construction, we take advantage of both structural and content features of Wikipedia and formalize real world objects in terms of concepts and relationships. For visual part, we train classifiers according to both global and local features, and generate middle-level concepts from the training images. A variant of the association rule mining algorithm is further developed to refine the built ontology. Our experimental results show that our method allows automatic construction of large-scale multi-modality ontology with high accuracy from challenging web image data set

Keywords

wikipedia, semantic concept, ontology, web image classification

Discipline

Databases and Information Systems | Systems Architecture

Research Areas

Data Science and Engineering

Publication

Informatica

Volume

34

Issue

3

First Page

297

Last Page

306

ISSN

0350-5596

Publisher

Slovene Society Informatika, Ljubljana

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.

Additional URL

https://www.informatica.si/index.php/informatica/article/view/304

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