eprintid: 6458
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/64/58
datestamp: 2023-11-09 16:18:14
lastmod: 2023-11-09 16:18:14
status_changed: 2023-11-09 16:06:47
type: conference_item
metadata_visibility: show
creators_name: Ullah, R.
creators_name: Said, A.B.M.
creators_name: Saleem, M.Q.
creators_name: Jaafar, J.
creators_name: Ullah, I.
title: Semantic ontology for annotated images
ispublished: pub
keywords: Information science; Ontology, Annotation; ConceptNet; LabelMe; Semantic ontology; Wordnet, Semantics
note: cited By 1; Conference of 3rd International Conference on Computer and Information Sciences, ICCOINS 2016 ; Conference Date: 15 August 2016 Through 17 August 2016; Conference Code:125433
abstract: In multimedia search the retrieval of an image from a huge data-set are surrounded with extensive widespread concerns. Without procedures, the content of multimedia for semantic-interpretation is not clearly or really available for use. Manual Annotation is the only simple technique that helps to overcome semantic-interpretation. However, manual Annotation is not only time wasting and costly but also encompassed with the absence of concept diversity and semantic gap. This paper extends a semantic ontology method to extract label terms of the annotated image. LabelMe is the annotated data-set of the so far annotated terms. It enhances terms with the support of Knowledge bases of WordNet and ConceptNet, particularly. It supplements the identical synonyms as well as semantically related terms. It further reduces the semantic interpretation as well as increases the Semantic ontology for that annotated term domain. The results of an experiment performed shows that, the synonym terms were 15 and conceptually terms were 79 added along the primary list. It represents concept diversity an enhancement of 119.13 unique terms in the original list. © 2016 IEEE.
date: 2016
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010456955&doi=10.1109%2fICCOINS.2016.7783250&partnerID=40&md5=120ca485a201b25d6a25830246038da0
id_number: 10.1109/ICCOINS.2016.7783250
full_text_status: none
publication: 2016 3rd International Conference on Computer and Information Sciences, ICCOINS 2016 - Proceedings
pagerange: 408-413
refereed: TRUE
isbn: 9781509051342
citation:   Ullah, R. and Said, A.B.M. and Saleem, M.Q. and Jaafar, J. and Ullah, I.  (2016) Semantic ontology for annotated images.  In: UNSPECIFIED.