Improving Statistical Multimedia Information Retrieval Model by using Ontology
March 21, 2017 Β· Declared Dead Β· π International Journal of Computer Applications ISSN No 0975 8887 Volume 94 No 2, May 2014
"No code URL or promise found in abstract"
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Authors
Gagandeep Singh Narula, Vishal Jain
arXiv ID
1703.07381
Category
cs.IR: Information Retrieval
Cross-listed
cs.AI
Citations
2
Venue
International Journal of Computer Applications ISSN No 0975 8887 Volume 94 No 2, May 2014
Last Checked
4 months ago
Abstract
A typical IR system that delivers and stores information is affected by problem of matching between user query and available content on web. Use of Ontology represents the extracted terms in form of network graph consisting of nodes, edges, index terms etc. The above mentioned IR approaches provide relevance thus satisfying users query. The paper also emphasis on analyzing multimedia documents and performs calculation for extracted terms using different statistical formulas. The proposed model developed reduces semantic gap and satisfies user needs efficiently.
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