Publication Type

Journal Article

Version

Postprint

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

Research Areas

Data Management and Analytics

Publication

Information Sciences

Volume

194

First Page

224

Last Page

239

ISSN

0020-0255

Identifier

10.1016/j.ins.2012.01.003

Publisher

Elsevier

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1016/j.ins.2012.01.003

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