Improving Statistical Multimedia Information Retrieval (MIR) Model by using Ontology

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.

• Publication year

  2017

• Venue

  arXiv: Information Retrieval

• Publication date

  2017-03-21

• Fields of study

  Computer Science

• Identifiers
  arXiv 1703.07381
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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