Toward bridging the annotation-retrieval gap in image search

Ritendra Datta; Weina Ge; Jia Li; James Z. Wang

doi:10.1109/MMUL.2007.67

Toward bridging the annotation-retrieval gap in image search

Ritendra Datta, Weina Ge, Jia Li, James Z. Wang

Research output: Contribution to journal › Article › peer-review

41 Scopus citations

Abstract

By combining novel statistical modeling techniques and the WordNet ontology, we offer a promising new approach to image search that uses automatic image tagging directly to perform retrieval.

Original language	English (US)
Pages (from-to)	24-35
Number of pages	12
Journal	IEEE Multimedia
Volume	14
Issue number	3
DOIs	https://doi.org/10.1109/MMUL.2007.67
State	Published - Jul 2007

All Science Journal Classification (ASJC) codes

Software
Signal Processing
Media Technology
Hardware and Architecture
Computer Science Applications

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10.1109/MMUL.2007.67

Cite this

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title = "Toward bridging the annotation-retrieval gap in image search",

abstract = "By combining novel statistical modeling techniques and the WordNet ontology, we offer a promising new approach to image search that uses automatic image tagging directly to perform retrieval.",

author = "Ritendra Datta and Weina Ge and Jia Li and Wang, {James Z.}",

note = "Funding Information: The research is supported in part by the US National Science Foundation, grants 0347148 and 0202007. We thank David M. Pennock at Yahoo! for providing some test images. We would also like to acknowledge the comments and constructive suggestions from reviewers.",

year = "2007",

month = jul,

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AU - Datta, Ritendra

AU - Ge, Weina

AU - Li, Jia

AU - Wang, James Z.

N1 - Funding Information: The research is supported in part by the US National Science Foundation, grants 0347148 and 0202007. We thank David M. Pennock at Yahoo! for providing some test images. We would also like to acknowledge the comments and constructive suggestions from reviewers.

PY - 2007/7

Y1 - 2007/7

N2 - By combining novel statistical modeling techniques and the WordNet ontology, we offer a promising new approach to image search that uses automatic image tagging directly to perform retrieval.

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JO - IEEE Multimedia

JF - IEEE Multimedia

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Toward bridging the annotation-retrieval gap in image search

Abstract

All Science Journal Classification (ASJC) codes

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