Title
A framework for linguistic relevance feedback in content-based image retrieval using fuzzy logic
Abstract
We describe a new approach for exploiting relevance feedback in content-based image retrieval (CBIR). In our approach to relevance feedback we try to capture more of the users' relevance judgments by allowing the use of natural language like comments on the retrieved images. Using methods from fuzzy logic and computational intelligence we are able to reflect these comments into new targets for searching the image database. Such enhanced information is utilized to develop a system that can provide more effective and efficient retrieval.
Year
DOI
Venue
2005
10.1016/j.ins.2005.03.004
Inf. Sci.
Keywords
Field
DocType
fuzzy logic,computational intelligence,linguistic relevance feedback,image database,enhanced information,content-based image retrieval,relevance feedback,new target,new approach,efficient retrieval,relevance judgment,natural language
Relevance feedback,Computer science,Image retrieval,Natural language processing,Artificial intelligence,Computational intelligence,Information retrieval,Fuzzy logic,Natural language,Relevance (information retrieval),Content-based image retrieval,Machine learning,Visual Word
Journal
Volume
Issue
ISSN
173
4
0020-0255
Citations 
PageRank 
References 
6
0.54
11
Authors
2
Name
Order
Citations
PageRank
Ronald R. Yager198521562.99
Frederick E. Petry256269.24