eprintid: 2222
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/22/22
datestamp: 2023-11-09 15:50:25
lastmod: 2023-11-09 15:50:25
status_changed: 2023-11-09 15:42:16
type: conference_item
metadata_visibility: show
creators_name: Irfanullah, 
creators_name: Aslam, N.
creators_name: Loo, J.
creators_name: Roohullah, 
creators_name: Loomes, M.
title: Adding semantics to the reliable object annotated image databases
ispublished: pub
keywords: Data sets; Image database; Information Extraction; Knowledge base; Manual annotation; Multimedia annotation; Multimedia information; Multimedia search; Retrieval performance; Semantic content; Semantic enrichment; Semantic gap; Semantic intensity; Semantic interpretation; Semantic similarity; Wordnet, Information retrieval systems, Semantics
note: cited By 6; Conference of 1st World Conference on Information Technology, WCIT-2010 ; Conference Date: 6 October 2010 Through 10 October 2010; Conference Code:84172
abstract: Semantically enriched multimedia information is crucial for equipping the kind of multimedia search potentials that professional searchers need. But the semantic interpretation of multimedia is obsolete without some mechanism for understanding semantic content that is not explicitly available. Manual annotation is the only source to overwhelming this, which is not only time consuming and costly but also lacks semantic enrichment in terms of concept diversity and concept enrichability. In this paper, we present semantically enhanced information extraction model that calculate the semantic intensity (SI) of each object in the image and then enhance the tagged concept with the assistance of lexical and conceptual knowledgebases. i.e. WordNet and ConceptNet. Noises, redundant and unusual words are then filtered out by means of various techniques like semantic similarity, stopwords and words unification. The experiment has been carried out on the LabelMe datasets. Results demonstrate the substantial improvement in terms of concept diversity, concept enrichment and retrieval performance. © 2010 Published by Elsevier Ltd.
date: 2011
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-79952514985&doi=10.1016%2fj.procs.2010.12.069&partnerID=40&md5=c4157321d77649f6cedbe2713311ee0e
id_number: 10.1016/j.procs.2010.12.069
full_text_status: none
publication: Procedia Computer Science
volume: 3
place_of_pub: Istanbul
pagerange: 414-419
refereed: TRUE
issn: 18770509
citation:   Irfanullah and Aslam, N. and Loo, J. and Roohullah and Loomes, M.  (2011) Adding semantics to the reliable object annotated image databases.  In: UNSPECIFIED.