Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

8-2010

Abstract

The overwhelming amounts of multimedia contents have triggered the need for automatically detecting the semantic concepts within the media contents. With the development of photo sharing websites such as Flickr, we are able to obtain millions of images with usersupplied tags. However, user tags tend to be noisy, ambiguous and incomplete. In order to improve the quality of tags to annotate web images, we propose an approach to build Semantic Fields for annotating the web images. The main idea is that the images are more likely to be relevant to a given concept, if several tags to the image belong to the same Semantic Field as the target concept. Semantic Fields are determined by a set of highly semantically associated terms with high tag co-occurrences in the image corpus and in different corpora and lexica such as WordNet and Wikipedia. We conduct experiments on the NUSWIDE web image corpus and demonstrate superior performance on image annotation as compared to the state-ofthe-art approaches.

Discipline

Databases and Information Systems | Graphics and Human Computer Interfaces

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of the 23rd International Conference on Computational Linguistics, Coling 2010, Beijing, August 23-27

Volume

2

First Page

1301

Last Page

1309

Identifier

10.5555/1944566.1944715

Publisher

ACM

City or Country

Beijing, China

Download

Share

COinS