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 But the semantic interpretation of multimedia is obsolete without some mechanism for understanding semantic content that is not explicitly available.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.