Publication Type
Journal Article
Version
publishedVersion
Publication Date
7-2012
Abstract
In many example-based information retrieval tasks, example query actually contains multiple sub-queries. For example, in 3D object retrieval, the query is an object described by multiple views. In content-based video retrieval, the query is a video clip that contains multiple frames. Without prior knowledge, the most intuitive approach is to treat the sub-queries equally without difference. In this paper, we propose a k-partite graph reinforcement approach to fuse these sub-queries based on the to-be-retrieved database. The approach first collects the top retrieved results. These results are regarded as pseudo-relevant samples and then a k-partite graph reinforcement is performed on these samples and the query. In the reinforcement process, the weights of the sub-queries are updated by an iterative process. We present experiments on 3D object retrieval and content-based video clip retrieval, and the results demonstrate that our method effectively boosts retrieval performance
Keywords
Multimedia, information retrieval, k-Partite, graph reinforcement, 3D object retrieval, Video retrieval
Discipline
Databases and Information Systems
Publication
Information Sciences
Volume
194
First Page
224
Last Page
239
ISSN
0020-0255
Identifier
10.1016/j.ins.2012.01.003
Publisher
Elsevier
Citation
GAO, Yue; WANG, Meng; Ji, Rongrong; ZHA, Zheng-Jun; and SHEN, Jialie.
k-Partite Graph Reinforcement and its Application in Multimedia Information Retrieval. (2012). Information Sciences. 194, 224-239.
Available at: https://ink.library.smu.edu.sg/sis_research/1497
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://doi.org/10.1016/j.ins.2012.01.003