Improving image sets through sense disambiguation and context ranking

Anthony Buck, Walterio Mayol-Cuevas

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)


Current approaches to automatic, class specific, image retrieval from the World Wide Web (WWW) by linguistic query often make use of an image’s internal characteristics and file meta-data to augment and improve result accuracy. We propose that, in extension, improvement can be achieved in relevance, noise-reduction and completeness through sense disambiguation and contextual meta-data prepossessing. Our schemes exploits a linguistic ontology identifying query relevant homographs used to construct sense specific keyword sets allowing for enhanced image search and result ranking via the calculation of relatedness between query homographs and image context prior to any additional filtering. Within the paper we investigate different schemes for keyword set construction; ontology exclusive and authority extended, along with three differing ranking mechanisms.
Translated title of the contributionImproving Image Sets Through Sense Disambiguation and Context Ranking
Original languageEnglish
Title of host publication2009 IEEE International Conference on Systems, Man and Cybernetics (SMC 2009)
Subtitle of host publicationProceedings of a meeting held 11-14 October 2009, San Antonio, Texas
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
ISBN (Print)9781424427932
Publication statusPublished - Jan 2010

Publication series

ISSN (Print)1062-922X


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