Title
Efficiently Support Concurrent Queries In Multiuser Cbir Systems
Keywords
Category search; Content-based image retrieval; Index structures; Relevance feedback; Target search
Abstract
Various techniques have been developed for different query types in content-based image retrieval systems such as sampling queries, constrained sampling queries, multiple constrained sampling queries, k-NN queries, constrained k-NN queries, and multiple localized k-NN queries. In this paper, we propose a generalized query model suitable for expressing queries of different types, and investigate efficient processing techniques for this new framework. We exploit sequential access and data sharing by developing new storage and query processing techniques to leverage inter-query concurrency. Our experimental results, based on the Corel dataset, indicate that the proposed optimization can significantly reduce average response time in a multiuser environment, and achieve better retrieval precision and recall compared to two recent techniques. © 2008 Springer Science + Business Media, LLC.
Publication Date
1-1-2009
Publication Title
Multimedia Tools and Applications
Volume
42
Issue
3
Number of Pages
273-293
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/s11042-008-0244-x
Copyright Status
Unknown
Socpus ID
84898009700 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84898009700
STARS Citation
Liu, Danzhou; Hua, Kien A.; and Yu, Ning, "Efficiently Support Concurrent Queries In Multiuser Cbir Systems" (2009). Scopus Export 2000s. 12309.
https://stars.library.ucf.edu/scopus2000/12309