Paper Info
Title
Towards Translation Of Tags In Large Annotated Image Collections
Abstract
This paper presents an approach for translation of tags in professional and social image databases, using an original lexical resource extracted from Wikipedia. The translation integrates a tag sense disambiguation algorithm based on WordNet and Wikipedia (as external resources defining word senses). Our disambiguation technique uses the Lesk algorithm, extended gloss overlaps and similarity measures in order to achieve successful resolution of lexical ambiguity and accurate translation of tags. We show how to involve Wikipedia as a source of translation correspondences since open WordNets are not available for most languages. Experimental results and performance evaluation show 97 % accuracy for professional images and 86 % accuracy for social images from Flickr. This translation technique can be applied by auto-tagging programs and information retrieval systems.
Year
DOI
Venue
2016
10.1007/978-3-319-44748-3_14
ARTIFICIAL INTELLIGENCE: METHODOLOGY, SYSTEMS, AND APPLICATIONS, AIMSA 2016
Keywords
Field
DocType
Multilingual language processing, Tag translation, Word sense disambiguation, Annotation disambiguation, Image auto-tagging
Information retrieval,Computer science,Natural language processing,Artificial intelligence,WordNet,Ambiguity,Social image,Word-sense disambiguation
Conference
Volume
ISSN
Citations 
9883
0302-9743
0
PageRank 
References 
Authors
0.34
7
3
Name
Order
Citations
PageRank
Olga Kanishcheva102.37
Galia Angelova221041.59
Stavri G. Nikolov324612.64