DocumentCode
15995
Title
Learning to Rerank Web Images
Author
Linjun Yang ; Hanjalic, Alan
Volume
20
Issue
2
fYear
2013
fDate
April-June 2013
Firstpage
13
Lastpage
21
Abstract
This article reviews recent advancements in developing approaches to Web image search reranking. The authors provide a categorization of related theories and algorithms and include a mathematical formulation, analysis, and discussion per category. They highlight the limitations of the existing approaches and make recommendations on what they believe to be the most critical research directions to improve the efficiency, effectiveness, and overall utility of Web image search reranking technology.
Keywords
image retrieval; search engines; Web image search reranking; mathematical formulation; search engine; Algorithm design and analysis; Information retrieval; Mathematical model; Search engines; Search methods; Search problems; Visualization; Algorithm design and analysis; Information retrieval; Mathematical model; Search engines; Search methods; Search problems; Visualization; Web technology; image search; multimedia; multimedia applications; search engine architecture; search reranking;
fLanguage
English
Journal_Title
MultiMedia, IEEE
Publisher
ieee
ISSN
1070-986X
Type
jour
DOI
10.1109/MMUL.2012.30
Filename
6212430
Link To Document