Improving Statistical Multimedia Information Retrieval Model by using Ontology

March 21, 2017 Β· Declared Dead Β· πŸ› International Journal of Computer Applications ISSN No 0975 8887 Volume 94 No 2, May 2014

πŸ‘» CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

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.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” Information Retrieval

Died the same way β€” πŸ‘» Ghosted